Статті в журналах: "Thermal object"

1

Morgan, D., and R. Henda. "Object-oriented Thermal Radiation Simulator." Education for Chemical Engineers 1, no. 1 (January 2006): 101–15. http://dx.doi.org/10.1205/ece06010.

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Kostyleva, Liliya Yu, Oleg V. Loginovskiy, Evgeniya A. Retc, and Igor M. Yachikov. "Possibilities of using mathematical models for thermal nondestructive testing of defects in multilayer bimetallic plates." Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control & Radioelectronics 22, no. 1 (January 2022): 53–64. http://dx.doi.org/10.14529/ctcr220104.

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There is an actual task of delamination detection in multilayer bimetallic materials. Various methods of nondestructive testing (NDT) are used to solve it, including the method of transient thermal NDT. This method consists in remote registration, visualization and analysis of thermal (temperature) fields, which depend on thermophysical and geometric characteristics, thermal effect capacity and internal structure features of the object. The internal structure defects cause the appearance of abnormal temperature zones on the object surface. Their analysis allows us to judge the presence of changes in the material as a whole or in individual areas. It is possible to understand whether there is a defect under the anomalous site, and what its parameters are, if there is an adequate mathematical model that theoretically describes the dependence of the measuring results on the properties of the object and the selected technological modes. This model is a significant component of thermal NDT systems. For the same object or process, a certain set of mathematical models can be compiled, differing in the number of factors taken into account, the assumptions made, the completeness and accuracy of the description of the state of the object or the conditions of the process. The set of factors is determined by the purpose of the study, and in order to unambiguously determine the model of the thermal state, it is necessary to describe the characteristics of the object (geometric shape and thermophysical characteristics of the material) and the heat exchange process (characteristics of heat sources, initial and boundary conditions). Aim. To analyze the existing mathematical models for the research object – a multilayer bimetallic plate with delaminations between the outer and inner layers, and to identify common approaches to modeling the processes of thermal NDT of multilayer objects. Materials and methods. The structure of the mathematical model of the thermal state of the object is determined. An analytical review of mathematical models of thermal NDT of multilayer objects is performed. Results. The requirements, assumptions and limitations for a mathematical model of thermal NDT of a multilayer bimetallic plate with delamination defects are formulated. Conclusion. On the basis of the considered approaches to the mathematical modeling of the thermal state of multilayer objects with ideal layers contact and delamination defects, the necessary factors for the development of a model for the transient thermal NDT processes of the studied objects are determined.

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3

Sadek, Toufic Abd El-Latif, Yousef Attalah, and Ghaleb Faour. "Optimal Timing for Capturing Satellite Thermal Images of Asphalt Object." European Scientific Journal, ESJ 12, no. 3 (January 30, 2016): 235. http://dx.doi.org/10.19044/esj.2016.v12n3p235.

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The best extraction of asphalt object from satellite thermal images is the aim of the study. The best original data of thermal images occurred at a specific times during the days of the year. by preventing the gaps in times which give the close and same brightness from different objects. Finally, to achieve easy and efficient extraction of asphalt object from the satellite thermal images and then better analysis. The study were done using seven sample objects, asphalt, concrete, metal, rock, dry soil, vegetation, and water, located at one place carefully investigated in a way that all the objects achieve the homogeneous in acquired data at same time and same weather conditions. The samples of the objects was at roof of building at position taking by global positioning system (GPS) which its geographical coordinates is: Latitude= 33° 37´ 25.402”, longitude= 35° 28´ 57.260", height= 600 m. It has been found that the first choice and the best time for capturing the satellite thermal images for better extraction of the asphalt object in february, march, November is at 1:00 pm, in august, october at 2:00 pm and coincide with the mean. In april, may at 3:00 pm, in june at 4:00 pm and not coincide with mean. It can be noted too that the time 1:00 pm is valid in all the months and coincide with mean.

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4

Mingalev, A. V., A. V. Belov, I. M. Gabdullin, R. R. Agafonova, and S. N. Shusharin. "Test-object recognition in thermal images." Computer Optics 43, no. 3 (June 2019): 402–11. http://dx.doi.org/10.18287/2412-6179-2019-43-3-402-411.

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The paper presents a comparative analysis of several methods for recognition of test-object position in a thermal image when setting and testing characteristics of thermal image channels in an automated mode. We consider methods of image recognition based on the correlation image comparison, Viola-Jones method, LeNet classificatory convolutional neural network, GoogleNet (Inception v.1) classificatory convolutional neural network, and a deep-learning-based convolutional neural network of Single-Shot Multibox Detector (SSD) VGG16 type. The best performance is reached via using the deep-learning-based convolutional neural network of the VGG16-type. The main advantages of this method include robustness to variations in the test object size; high values of accuracy and recall parameters; and doing without additional methods for RoI (region of interest) localization.

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5

Pavlovic, Milan, Ivan Ciric, Danijela Ristic-Durrant, Vlastimir Nikolic, Milos Simonovic, Milica Ciric, and Milan Banic. "Advanced thermal camera based system for object detection on rail tracks." Thermal Science 22, Suppl. 5 (2018): 1551–61. http://dx.doi.org/10.2298/tsci18s5551p.

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In this paper, an advanced thermal camera-based system for detection of objects on rail tracks is presented. Developed system is powered by advanced image processing algorithm, in order to achieve greater reliability and robustness, and tested on set of infrared images captured at night conditions. The goal of this system is to detect objects on rail tracks and next to them and estimate distances between camera stand and detected objects. For that purpose, different edge detection methods are tested, and finally Canny edge detector is selected for rail track detection and for determination of region of interest, further used for analysis in object detection process. In determined region of interest, region-based segmentation is used for object detection. For estimation of distances between camera stand and detected objects, homography based method is used. Validation of estimated distances is done, in respect to real measured distances from camera stand to objects (humans) involved in experiment. Distances are estimated with a maximum error of 2%. System can provide reliable object detection, as well as distance estimation, and for improved robustness and adaptability, artificial intelligence tools can be used.

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6

Brickner, Michael S., and Amir Zvuloni. "The Effect of Polarity on Object Recognition in Thermal Images." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 37, no. 1 (October 1993): 137–41. http://dx.doi.org/10.1177/154193129303700132.

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Thermal imaging (TI) systems, transform the distribution of relative temperatures in a scene into a visible TV image. TIs differ significantly from regular TV images. Most TI systems allow their operators to select preferred polarity which determines the way in which gray shades represent different temperatures. Polarity may be set to either black hot (BH) or white hot (WH). The present experiments were designed to investigate the effects of polarity on object recognition performance in TI and to compare object recognition performance of experts and novices. In the first experiment, twenty flight candidates were asked to recognize target objects in 60 dynamic TI recordings taken from two different TI systems. The targets included a variety of human placed and natural objects. Each subject viewed half the targets in BH and the other half in WH polarity in a balanced experimental design. For 24 out of the 60 targets one direction of polarity produced better performance than the other. Although the direction of superior polarity (BH or WH better) was not consistent, the preferred representation of the target object was very consistent. For example, vegetation was more readily recognized when presented as dark objects on a brighter background. The results are discussed in terms of importance of surface determinants versus edge determinants in the recognition of TI objects. In the second experiment, the performance of 10 expert TI users was found to be significantly more accurate but not much faster than the performance of 20 novice subjects.

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7

Головин, Д. Ю., А. И. Тюрин, А. А. Самодуров та Ю. И. Головин. "Определение температуропроводности материалов методом нестационарного точечного нагрева". Письма в журнал технической физики 46, № 1 (2020): 39. http://dx.doi.org/10.21883/pjtf.2020.01.48863.18052.

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Express thermographic method for measuring thermal diffusivity of thin flat objects is described in the paper. It could be considered as modification or a branch of laser flash method, however it does not require sample cutting or two side access to the object. The method comprises step-like heating of the small area (~ 0.1 mm2) at the object surface by focused laser beam and continuous recording temperature distribution at the surface by thermal camera. Developed data processing technique does not require information about absolute temperatures or absorbed energy for determination of thermal diffusivity coefficient.

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8

Gritzo, Louis A., and Vernon F. Nicolette. "Coupling of Large Fire Phenomenon with Object Geometry and Object Thermal Response." Journal of Fire Sciences 15, no. 6 (November 1997): 427–42. http://dx.doi.org/10.1177/073490419701500601.

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The effect of an object in or near a large fire on the physical pro cesses which result in the heat flux from the fire is defined by the object geometry and temperature, and therefore the fire phenomena and the object physical states can be coupled. Two primary modes of coupling, radiative and convective, and their relative influence on heat flux, are investigated using observations from ex perimental data and numerical simulations. Radiative coupling occurs when a comparatively cold object reduces the incident heat flux (by up to 65%) due to radiative cooling of nearby media. Convective coupling includes: (1) changes in the geometry of the flame zone, and (2) object-induced turbulence which alters and often enhances the flow, mixing, and, hence, combustion processes within the fire. Increases in the heat flux approaching a factor of three have been observed due to these phenomena.

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9

Ho, Hsin-Ni, Hiu Mei Chow, Sayaka Tsunokake, and Warrick Roseboom. "Thermal-Tactile Integration in Object Temperature Perception." IEEE Transactions on Haptics 12, no. 4 (October 1, 2019): 594–603. http://dx.doi.org/10.1109/toh.2019.2894153.

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10

Xia, Haiping, Yunhao Chen, Jinling Quan, and Jing Li. "Object-Based Window Strategy in Thermal Sharpening." Remote Sensing 11, no. 6 (March 15, 2019): 634. http://dx.doi.org/10.3390/rs11060634.

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The trade-off between spatial and temporal resolutions has led to the disaggregation of remotely sensed land surface temperatures (LSTs) for better applications. The window used for regression is one of the primary factors affecting the disaggregation accuracy. Global window strategies (GWSs) and local window strategies (LWSs) have been widely used and discussed, while object-based window strategies (OWSs) have rarely been considered. Therefore, this study presents an OWS based on a segmentation algorithm and provides a basis for selecting an optimal window size balancing both accuracy and efficiency. The OWS is tested with Landsat 8 data and simulated data via the “aggregation-then-disaggregation” strategy, and compared with the GWS and LWS. Results tested with the Landsat 8 data indicate that the proposed OWS can accurately and efficiently generate high-resolution LSTs. In comparison to the GWS, the OWS improves the mean accuracy by 0.19 K at different downscaling ratios, in particular by 0.30 K over urban areas; compared with the LWS, the OWS performs better in most cases but performs slightly worse due to the increasing downscaling ratio in some cases. Results tested with the simulated data indicate that the OWS is always superior to both GWS and LWS regardless of the downscaling ratios, and the OWS improves the mean accuracy by 0.44 K and 0.19 K in comparison to the GWS and LWS, respectively. These findings suggest the potential ability of the OWS to generate super-high-resolution LSTs over heterogeneous regions when the pixels within the object-based windows derived via segmentation algorithms are more homogenous.

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11

Nilsson, B., and J. Eborn. "Object-oriented modelling of thermal power plants." Mathematical and Computer Modelling of Dynamical Systems 4, no. 3 (January 1998): 207–18. http://dx.doi.org/10.1080/13873959808837078.

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12

Bieszczad, Grzegorz, Tomasz Sosnowski, Krzysztof Sawicki, Sławomir Gogler, Andrzej Ligienza, and Mariusz Mścichowski. "A Network of Miniature Thermal Imaging Sensors for Object Detection and Tracking." Pomiary Automatyka Robotyka 25, no. 4 (December 7, 2021): 57–66. http://dx.doi.org/10.14313/par_242/57.

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This paper presents a concept and implementation of an infrared imaging sensor network for object localization and tracking. The sensor network uses multiple low-resolution (80× 80 pixels) microbolometric thermal cameras to detect, track and locate an object within the area of observation. The network uses information simultaneously acquired from multiple sensors to detect and extract additional information about object’s location. The use of thermal-imaging systems responsive to objects’ natural infrared radiation, makes the system resistant to external illumination and environmental conditions. At the same time, the use of infrared sensor requires application of specially designed, dedicated image processing techniques appropriate for this kind of sensor. The paper describes: image processing techniques, means of object localization, accuracy measurements, comparison to other known solutions and final conclusions.

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13

Sardjito and Nani Yuningsih. "Determination of Object Temperature Influenced by Ambient Temperature as a Solution of Newton’s Law of Cooling or Heating Rates." South Florida Journal of Development 2, no. 3 (July 28, 2021): 4563–73. http://dx.doi.org/10.46932/sfjdv2n3-058.

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Thermal physics experiments often require accurate data about the thermal condition of the observed object so that its temperature should be measured. The object temperature, which is observed directly using a measuring instrument, does not represent its actual thermal condition because there is an influence of the object temperature and the ambient temperature differences, especially if the object is not in adiabatic isolation. Newton’s Law on cooling or heating rate is used to determine the actual object temperature if the ambient influence is eliminated. The method used in this research is matching analyses between mathematical solutions and empirical data. In thermal physics experiments in laboratories, particularly in the Basic Physics Laboratory, the influence of ambient temperature-known as Newton Correction-often uses a linear temperature-change approach to time. Thus, an analysis of the differential equation model of Newton’s Law of cooling and heating rates is carried out. The result shows that the objects temperature function over time is in the form of an exponential function, both for a constant ambient temperature, and an ambient temperature that changes over time. The result of this analysis is also in line with the experimental data of the Mechanical Heat Equivalence experiment conducted in the Basic Physics Laboratory of Bandung State Polytechnic.

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14

Ligocki, Adam, Ales Jelinek, Ludek Zalud, and Esa Rahtu. "Fully Automated DCNN-Based Thermal Images Annotation Using Neural Network Pretrained on RGB Data." Sensors 21, no. 4 (February 23, 2021): 1552. http://dx.doi.org/10.3390/s21041552.

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One of the biggest challenges of training deep neural network is the need for massive data annotation. To train the neural network for object detection, millions of annotated training images are required. However, currently, there are no large-scale thermal image datasets that could be used to train the state of the art neural networks, while voluminous RGB image datasets are available. This paper presents a method that allows to create hundreds of thousands of annotated thermal images using the RGB pre-trained object detector. A dataset created in this way can be used to train object detectors with improved performance. The main gain of this work is the novel method for fully automatic thermal image labeling. The proposed system uses the RGB camera, thermal camera, 3D LiDAR, and the pre-trained neural network that detects objects in the RGB domain. Using this setup, it is possible to run the fully automated process that annotates the thermal images and creates the automatically annotated thermal training dataset. As the result, we created a dataset containing hundreds of thousands of annotated objects. This approach allows to train deep learning models with similar performance as the common human-annotation-based methods do. This paper also proposes several improvements to fine-tune the results with minimal human intervention. Finally, the evaluation of the proposed solution shows that the method gives significantly better results than training the neural network with standard small-scale hand-annotated thermal image datasets.

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15

Montezuma, Sandra R., Susan Y. Sun, Arup Roy, Avi Caspi, Jessy D. Dorn, and Yingchen He. "Improved localisation and discrimination of heat emitting household objects with the artificial vision therapy system by integration with thermal sensor." British Journal of Ophthalmology 104, no. 12 (March 9, 2020): 1730–34. http://dx.doi.org/10.1136/bjophthalmol-2019-315513.

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AimTo demonstrate the potential clinically meaningful benefits of a thermal camera integrated with the Argus II, an artificial vision therapy system, for assisting Argus II users in localising and discriminating heat-emitting objects.MethodsSeven blind patients implanted with Argus II retinal prosthesis participated in the study. Two tasks were investigated: (1) localising up to three heat-emitting objects by indicating the location of the objects and (2) discriminating a specific heated object out of three presented on a table. Heat-emitting objects placed on a table included a toaster, a flat iron, an electric kettle, a heating pad and a mug of hot water. Subjects completed the two tasks using the unmodified Argus II system with a visible-light camera and the thermal camera-integrated Argus II.ResultsSubjects more accurately localised heated objects displayed on a table (p=0.011) and discriminated a specific type of object (p=0.005) presented with the thermal camera integrated with the Argus II versus the unmodified Argus II camera.ConclusionsThe thermal camera integrated with the artificial vision therapy system helps users to locate and differentiate heat-emitting objects more precisely than a visible light sensor. The integration of the thermal camera with the Argus II may have significant benefits in patients’ daily life.

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Kniaz, V. V., and P. Moshkantseva. "OBJECT RE-IDENTIFICATION USING MULTIMODAL AERIAL IMAGERY AND CONDITIONAL ADVERSARIAL NETWORKS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIV-2/W1-2021 (April 15, 2021): 131–36. http://dx.doi.org/10.5194/isprs-archives-xliv-2-w1-2021-131-2021.

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Abstract. Object Re-Identification (ReID) is the task of matching a given object in the new environment with its image captured in a different environment. The input for a ReID method includes two sets of images. The probe set includes one or more images of the object that must be identified in the new environment. The gallery set includes images that may contain the object from the probe image. The ReID task’s complexity arises from the differences in the object appearance in the probe and gallery sets. Such difference may originate from changes in illumination or viewpoint locations for multiple cameras that capture images in the probe and gallery sets. This paper focuses on developing a deep learning ThermalReID framework for cross-modality object ReID in thermal images. Our framework aims to provide continuous object detection and re-identification while monitoring a region from a UAV. Given an input probe image captured in the visible range, our ThermalReID framework detects objects in a thermal image and performs the ReID. We evaluate our ThermalReID framework and modern baselines using various metrics. We use the IoU and mAP metrics for the object detection task. We use the cumulative matching characteristic (CMC) curves and normalized area-under-curve (nAUC) for the ReID task. The evaluation demonstrated encouraging results and proved that our ThermalReID framework outperforms existing baselines in the ReID accuracy. Furthermore, we demonstrated that the fusion of the semantic data with the input thermal gallery image increases the object detection and localization scores. We developed the ThermalReID framework for cross-modality object re-identification. We evaluated our framework and two modern baselines on the task of object ReID for four object classes. Our framework successfully performs object ReID in the thermal gallery image from the color probe image. The evaluation using real and synthetic data demonstrated that our ThermalReID framework increases the ReID accuracy compared to modern ReID baselines.

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17

Карпов, Д., and Denis Karpov. "THE ACTIVE METHOD OF CONTROL THE THERMAL CONDUCTIVITY OF BUILDING MATERIALS AND PRODUCTS." Bulletin of Belgorod State Technological University named after. V. G. Shukhov 4, no. 7 (July 21, 2019): 57–62. http://dx.doi.org/10.34031/article_5d35d0b79c34c5.75173950.

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Thermal control refers to non-destructive testing methods. There are passive and active thermal non-destructive testing. With passive thermal control, the test object is characterized by a temperature field formed during its operation. With active thermal control, an additional source of thermal stimulation of the controlled object is used. Thermal control is widely used in various sectors of construction, energy, engineering and transport. The paper proposes a variant of active thermal non-destructive control of thermal conductivity coefficient of building materials and products on the example of a fragment of a building structure made of silicate bricks. The controlled object is subjected to thermal stimulation by an external source of thermal energy until the fixed thermal regime. Thermography of the test object surfaces is performed. The average values of surfaces temperature or individual sections of controlled object are calculated. The heat equation determines a controlled parameter - the heat coefficient of the object under control. The thermal resistance (heat transfer resistance) of the controlled object is calculated with a known coefficient of thermal conductivity. The heat transfer coefficient is calculated with a known coefficient of thermal resistance (heat transfer resistance). The method is implemented in the laboratory. It can be used in field and operating conditions for accurate and rapid determination of the key thermal properties of building materials and products.

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18

BOSCH-RAMON, VALENTÍ. "NON-THERMAL EMISSION FROM GALACTIC JETS." International Journal of Modern Physics: Conference Series 08 (January 2012): 84–95. http://dx.doi.org/10.1142/s201019451200445x.

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Jets are ubiquitous in the Universe. They are collimated outflows whose origin is associated to an accretion disc and a central object, and can be very powerful non-thermal emitters. Jets form in active galactic nuclei, gamma-ray bursts, microquasars, and young stellar objects. Galactic jets emitting non-thermal emission are typically associated to microquasars, although the jets of massive young stellar objects are also non-thermal sources. The production of non-thermal radiation, in particular radio synchrotron emission, is a clear indication that particle acceleration is taking place in the source, which hints to the generation of photons even at high energies. In this work, we will discuss the emitting sites in, or related to, microquasar jets, and briefly comment on the possibility of high-energy emission in jets from young stellar objects.

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19

Karpov, Denis, Mikhail Pavlov, Liliya Mukhametova, and Anton A. Mikhin. "Features and results of assessment the thermal conductivity of building materials and products by the active method of thermal non-destructive testing." E3S Web of Conferences 220 (2020): 01053. http://dx.doi.org/10.1051/e3sconf/202022001053.

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Thermal control (passive and active) is a non-destructive testing method. During passive thermal control, the test object is characterized by a temperature field formed during its operation. In active thermal control, the test object is additionally thermally stimulated. This technique is widely used in various areas of construction, energy, mechanical engineering, transport. This paper proposes a variant of active thermal non-destructive assessment of the thermal conductivity coefficient of building materials and products on the example of a fragment of a building structure made of silicate bricks. The test object is subjected to thermal stimulation by an external source of thermal energy before reaching a steady-state thermal regime. Thermography of the test object surfaces is carried out. The average integral temperatures of surfaces or individual sections of the test object are calculated. The coefficient of thermal conductivity of the test object is determined, which is used to calculate its thermal resistance (resistance to heat transfer). After that, the coefficient of heat transfer is calculated. The method was implemented in laboratory conditions. It can be used in natural and operational conditions for accurate and quick determination of the key thermophysical properties of building materials and products.

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Zhang, Nai Yan, Jiang Yu, and Juan Zhang. "Study on Superabsorbent Material in Thermal Infrared Camouflage." Advanced Materials Research 941-944 (June 2014): 370–73. http://dx.doi.org/10.4028/www.scientific.net/amr.941-944.370.

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Objectives, which is motional on the batter field, such as vehicles, tanks, planes, warships, firing cannons, etc. They are all active objects. On the surface of these objects there have very higher temperatures than around background, they have special pictures, and are easy found by thermal infrared reconnaissance systems. In this study, itaconic acid (IA) was co-polymerized with N, N-diethylacrylamide (DEA) monomer to improve the swelling behavior and the total absorbing water. These copolymer materials were prepared by changing the initial DEA/IA molar ratio and total monomer concentration. The chemical structure of materials was characterized by fourier transform infrared (FTIR) spectroscopy. In comparison with the PDEA hydrogel, the equilibrium swelling ratio (ESR) of the materials increase with the increase of IA content in the feed and the swelling dynamics behaviors of the different composition ratios of the P(DEA-co-IA) materials on the different temperatures was investigated in detail. Using the big hot-inertia of water, the superabsorbent material of the object surface is propitious to debase the object temperature, which suggests that these materials have potential application as thermal infrared camouflage materials.

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Mizginov, V. A., and V. V. Kniaz. "EVALUATING THE ACCURACY OF 3D OBJECT RECONSTRUCTION FROM THERMAL IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W18 (November 29, 2019): 129–34. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w18-129-2019.

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Abstract. Thermal cameras are increasingly used in many photogrammetric and computer vision tasks. Nowadays it is possible to detect and recognize objects in infrared images, to solve such tasks as pedestrian detection (Huckridge et al., 2016), security applications, and autonomous driving (Wenbin, Li et al., 2017). Nevertheless, some tasks that are easily solved in the visible range data are still challenging to achieve in the infrared range. Reconstruction of a 3D object model from infrared images is challenging due to the low contrast of the original infrared image, noise of the sensor, and the absence of feature points on the image. Nevertheless, thermal cameras have their advantages, which make them popular for solving practical problems. Firstly, thermal cameras can be used in degraded environments (smoke, fog, precipitation, low light conditions). Secondly, infrared images can be fused with color images (Gao et al., 2013) to increases the system’s performance.This paper is focused on the evaluation of accuracy of 3D object reconstruction from thermal images. The evaluation of the accuracy is threefold. Firstly, we train four stereo matching methods (CAE, LF-Net, SURF, and SIFT) on the MVSIR dataset (Knyaz et al., 2017) and our new ThermalPatches dataset. We used two RTX 2080 Ti GPUs and the PyTorch library for the training. Secondly, we evaluate the matching score for the selected methods. Finally, we perform 3D object reconstruction using the SfM (Remondino et al., 2014) approach and matches for each method. We compare the object space accuracy of the resulting surfaces to the ground-truth 3D models generated with a structured light 3D scanner.

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De Sanctis, M. C., M. T. Capria, A. Coradini, and R. Orosei. "Thermal Evolution of the Centaur Object 5145 Pholus." Astronomical Journal 120, no. 3 (September 2000): 1571–78. http://dx.doi.org/10.1086/301512.

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23

Russell, R. Andrew. "Thermal sensor for object shape and material constitution." Robotica 6, no. 1 (January 1988): 31–34. http://dx.doi.org/10.1017/s0263574700003568.

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SUMMARYThis paper describes a novel tactile sensor array designed to provide information about the material constitution and shape of objects held by a robot manipulator. The sensor is modeled on the thermal touch sense which enables humans to distinguish between different materials based on how warm or cold they feel. Some results are presented and methods of analysing the sensor data are discussed.

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Shaw, Adam, Nadine M. Pay, Roy C. Preston, and Antony D. Bond. "Proposed standard thermal test object for medical ultrasound." Ultrasound in Medicine & Biology 25, no. 1 (January 1999): 121–32. http://dx.doi.org/10.1016/s0301-5629(98)00136-7.

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25

Dai, Chuanshan, Xin Guo, Jinhua Lu, and Haiyan Lei. "Thermal Conductivity Measurement of A Bar-like Object." Energy Procedia 142 (December 2017): 3975–81. http://dx.doi.org/10.1016/j.egypro.2017.12.306.

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Makarova, L. A., and E. L. Nevzgodina. "Thermal Energy as an Object of Civil Rights." Herald of Omsk University. Series Law 17, no. 2 (2020): 58–67. http://dx.doi.org/10.24147/1990-5173.2020.17(2).58-67.

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Miller, David A. B., Linxiao Zhu, and Shanhui Fan. "Universal modal radiation laws for all thermal emitters." Proceedings of the National Academy of Sciences 114, no. 17 (April 10, 2017): 4336–41. http://dx.doi.org/10.1073/pnas.1701606114.

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We derive four laws relating the absorptivity and emissivity of thermal emitters. Unlike the original Kirchhoff radiation law derivations, these derivations include diffraction, and so are valid also for small objects, and can also cover nonreciprocal objects. The proofs exploit two recent approaches. First, we express all fields in terms of the mode-converter basis sets of beams; these sets, which can be uniquely established for any linear optical object, give orthogonal input beams that are coupled one-by-one to orthogonal output beams. Second, we consider thought experiments using universal linear optical machines, which allow us to couple appropriate beams and black bodies. Two of these laws can be regarded as rigorous extensions of previously known laws: One gives a modal version of a radiation law for reciprocal objects—the absorptivity of any input beam equals the emissivity into the “backward” (i.e., phase-conjugated) version of that beam; another gives the overall equality of the sums of the emissivities and the absorptivities for any object, including nonreciprocal ones. The other two laws, valid for reciprocal and nonreciprocal objects, are quite different from previous relations. One shows universal equivalence of the absorptivity of each mode-converter input beam and the emissivity into its corresponding scattered output beam. The other gives unexpected equivalences of absorptivity and emissivity for broad classes of beams. Additionally, we prove these orthogonal mode-converter sets of input and output beams are the ones that maximize absorptivities and emissivities, respectively, giving these beams surprising additional physical meaning.

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Yamamoto, Akio, Hiroaki Yamamoto, Benjamin Cros, Hironori Hashimoto, and Toshiro Higuchi. "Thermal Tactile Presentation Based on Prediction of Contact Temperature." Journal of Robotics and Mechatronics 18, no. 3 (June 20, 2006): 226–34. http://dx.doi.org/10.20965/jrm.2006.p0226.

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The thermal sensation corresponding to the touching of an object is one of the most important factors in material recognition. In virtual reality or tele-operation systems, thermal display functions should be embedded in order to obtain satisfactory realism. Since our skin sensors are sensitive to rapid changes in temperature, thermal sensations are thought to arise mainly from the rapid temperature decrease that occurs at the moment of contact between our fingers and an object. Based on this consideration, the present paper proposes a new control method for thermal tactile display to simulate the temperature decrease at the moment of contact. The proposed method controls a thermal tactile display based on the prediction of contact temperature, so that the correct temperature decrease can be produced at the fingertip surface. In addition, we herein report an additional method by which to optimize the thermal rendering for individual subjects. In the optimization, the thermal property of each subject is estimated immediately prior to thermal presentation. The experimental results reveal that the tendency of material discrimination for the thermal tactile display is similar to that for real objects, indicating the validity of the proposed method.

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29

Krstulović-Opara, Lovre, Endri Garafulić, Branko Klarin, and Željko Domazet. "Application of Gradient Based IR Thermography to the GRP Structures Inspection." Key Engineering Materials 488-489 (September 2011): 682–85. http://dx.doi.org/10.4028/www.scientific.net/kem.488-489.682.

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The article presents application of non destructive testing method based on the pulse heating infrared thermography used to detect material anomalies for the case of glass reinforced polymer structures. The goal of presented research, based on the thermal gradient approach, is to establish the procedure capable of filtering out anomalies from other thermal influences caused by thermal reflections of surrounding objects, geometry influences and heat flows for observed object.

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30

Wang, Yi Wen, Huan Rui Hao, Xian Li Liu, and Cai Xu Yue. "Emissivity Calibration and Research of Infrared Image Processing in the Cutting Temperature Test." Applied Mechanics and Materials 10-12 (December 2007): 928–33. http://dx.doi.org/10.4028/www.scientific.net/amm.10-12.928.

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It is by the emissivity of the goal objects and the noise problem of the high temperature images that people are puzzled during the course of the cutting temperature tested by the application of thermal imaging device. By using thermocouples, and getting the comparison of thermocouples and the thermal imaging system temperature, we calibrate object emissivity, handle the image noise by improved median method, carry on the edge extraction of image, obtain the temperature of measured objects, and finally confirm the accuracy of the data got by the thermal imaging device with contact measurement.

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Hoegner, L., and U. Stilla. "BUILDING FACADE OBJECT DETECTION FROM TERRESTRIAL THERMAL INFRARED IMAGE SEQUENCES COMBINING DIFFERENT VIEWS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-3/W4 (March 11, 2015): 55–62. http://dx.doi.org/10.5194/isprsannals-ii-3-w4-55-2015.

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This paper discusses the automatic texturing of building facades from thermal infrared image sequences. A fully automatic method is presented to refine GPS based positions estimating relative orientations of the image sequences including a given building model in a bundle adjustment process. The resulting refined orientation parameters are used to extract partial facade textures from all images and all sequences. The resulting partial textures of every sequence are combined to get complete facade textures in the thermal infrared domain. Textures from different image sequences are combined for object detection and extraction. These sequences are acquired either at different times for different radiometric thermal behavior of facade objects or with different viewing directions for objects located before or behind the facade plane.

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32

Sivakov, V. V., S. S. Gryadunov, and R. Yu Derevyagin. "APPLICATION OF THERMAL IMAGES FOR DIAGNOSING TRUCKS." REPAIR RECONDITIONING MODERNIZATION, no. 2 (February 2022): 16–21. http://dx.doi.org/10.31044/1684-2561-2022-0-2-16-21.

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The object of the research is the use of thermal imagers for quick diagnostics of assemblies and parts heated during normal operation of the vehicle. It is shown that the use of a thermal imager makes it possible to obtain the temperature field on the object under study and, based on a comparison of actual temperatures and temperatures corresponding to normal operation, to assess the technical condition of the object.

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Akshatha, K. R., A. Kotegar Karunakar, Satish B. Shenoy, Abhilash K. Pai, Nikhil Hunjanal Nagaraj, and Sambhav Singh Rohatgi. "Human Detection in Aerial Thermal Images Using Faster R-CNN and SSD Algorithms." Electronics 11, no. 7 (April 6, 2022): 1151. http://dx.doi.org/10.3390/electronics11071151.

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The automatic detection of humans in aerial thermal imagery plays a significant role in various real-time applications, such as surveillance, search and rescue and border monitoring. Small target size, low resolution, occlusion, pose, and scale variations are the significant challenges in aerial thermal images that cause poor performance for various state-of-the-art object detection algorithms. Though many deep-learning-based object detection algorithms have shown impressive performance for generic object detection tasks, their ability to detect smaller objects in the aerial thermal images is analyzed through this study. This work carried out the performance evaluation of Faster R-CNN and single-shot multi-box detector (SSD) algorithms with different backbone networks to detect human targets in aerial view thermal images. For this purpose, two standard aerial thermal datasets having human objects of varying scale are considered with different backbone networks, such as ResNet50, Inception-v2, and MobileNet-v1. The evaluation results demonstrate that the Faster R-CNN model trained with the ResNet50 network architecture out-performed in terms of detection accuracy, with a mean average precision (mAP at 0.5 IoU) of 100% and 55.7% for the test data of the OSU thermal dataset and AAU PD T datasets, respectively. SSD with MobileNet-v1 achieved the highest detection speed of 44 frames per second (FPS) on the NVIDIA GeForce GTX 1080 GPU. Fine-tuning the anchor parameters of the Faster R-CNN ResNet50 and SSD Inception-v2 algorithms caused remarkable improvement in mAP by 10% and 3.5%, respectively, for the challenging AAU PD T dataset. The experimental results demonstrated the application of Faster R-CNN and SSD algorithms for human detection in aerial view thermal images, and the impact of varying backbone network and anchor parameters on the performance improvement of these algorithms.

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Feng, Dong Wu, Gui Li Xu, Biao Wang, Yu Peng Tian, and Yong Qiang Ye. "Optimum Design of the Cooperation Objective for Computer Vision-Based UAV Autonomous Landing." Advanced Materials Research 718-720 (July 2013): 1221–27. http://dx.doi.org/10.4028/www.scientific.net/amr.718-720.1221.

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In this paper, a novel approach to improve the infrared cooperative object for accurately landing is proposed. We present the designed cooperative object system and the blurring around the object when its working, and then begin our basic research on the cooperative object. We analyzed the formation principle of thermal blurring in the infrared imaging mechanism. After a detailed analysis infrared thermal blurring from thermodynamic principle, we derived the main factors of the infrared thermal blurring, and used Fluent simulation software to simulate the formation of thermal blurring. At the same time, the paper optimized the design of cooperation target to reduce thermal blurring. Experiments show that the optimum design of the cooperation objectives thermal blurring has significantly improved compared with some other methods.

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Dhaundiyal, Alok, and Laszlo Toth. "Modelling of a Torrefaction Process Using Thermal Model Object." Energies 14, no. 9 (April 27, 2021): 2481. http://dx.doi.org/10.3390/en14092481.

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So far, the torrefaction process has been merely discussed based on the physical and chemical characteristics of the final product, but the mechanism has not been yet pondered and investigated. Thus far, microwave torrefaction has been predominately used for thermal pre-treatment; therefore, a paradigm shift in the methodology has been introduced by using a Joule heating system. The article mainly focuses on the thermal engineering aspect of the torrefaction process. The densified black pine underwent thermal pre-treatment at a temperature of 523 K. The furnace used for torrefaction was initially improvised to carry out thermal degradation at quasi-static/dynamic conditions. A 3D PDE thermal model was developed to determine the numerical solution and temperature distribution across a black pine pellet. To compare the effect of the linear ramping profile, time-dependent as well as fixed Dirichlet conditions were applied to the proposed model. The mass distribution, duration of the torrefaction process, the effect of Nusselt and Reynold’s number of inert gas, and thermal history are some of the factors whose influence on the numerical solution was investigated. The simulation of thermal pre-treatment and its effect on the heat transfer characteristic was examined with help of a PDE thermal model, whereas the numerical solution of diffusion of the product of reactions was determined by solving the partial differential equations with the help of the discretisation method (PDEPE). The densification of black pine was performed in a ring die, whereas initial milling of biomass was carried out using a 1.5 mm sieve size. The system was found to have a homogeneous distribution in energy and temperature with time, whereas the amplitude of heat flux along the radial direction was reduced by 15% if the same pellet underwent torrefaction for a duration of 5 min in dynamic mode. Similarly, a 64.46% drop in amplitude of heat flux along the azimuth plane could be seen while performing torrefaction in a time-dependent thermal history. However, the relative amplitude of the heat flux at the centre of the pellet was estimated to be lowered by 98.41% along the vertical axis for heating a pellet in a quasi-static condition. The net change in the mass fraction of carbon dioxide across the boundary film was seen to be 40% higher than that of carbon monoxide. The rate of change of mass fraction of carbon monoxide across the boundary film was increased by 7–11% with the increase in torrefaction time. A 6.8% rise in the evaporation of water was noticed during the first half interval of torrefaction (from 5 min to 10 min). In the second half, from 10 min to 15 min, it was merely increased by 5.8%. A relative drop of 17.24% in water evaporation was estimated in the dynamic state of the system.

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36

Voskoboynik, E. "The implementation of a digital system for automatic continuous control object, based on a physical model of the object using a thermal Scada Zenon system." Collection of Research Papers of the National Mining University 64 (2021): 253–63. http://dx.doi.org/10.33271/crpnmu/64.253.

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Purpose. Develop a methodology for the implementation of digital control systems for continuous objects on a personal computer, which should provide: bringing the temperature in the chamber to a given value at a given range of air flow in the system; maintaining the temperature in the chamber at a given level at a given range of air flow in the system; visualization and control of the stand of the thermal object; control of fan speed in order to create a disturbing effect; registration of process parameters in the thermal object. The methods. The development is carried out through the phased implementation of a digital control system for a continuous object, implemented on a personal computer. The proposed approach consists of the main stages: a controller is synthesized in a continuous form, which implements the proportional-integral-differential (PID) control law. The simulation of the obtained system is performed in the mathematical package MATLAB. At the next stage on the personal computer the software implementation of the synthesized digital regulator is executed. At the last stage, the hardware elements of the control system were developed and implemented. Findings. The use of this approach in the development of a system of automatic control of a continuous object on the basis of a thermal object allows you to effectively create a complete hardware and software part of digital SAC using Scada system Zenon. This will significantly reduce the duration and cost of commissioning of ACS in production conditions at the actual control facility. Which makes it possible to significantly reduce the duration and cost of commissioning of ACS in production conditions at the actual control facility. The originality. For the first time, a method of creating a control system for thermal objects, based on programmable logic controller with the synthesis of the system in the mathematical package MATLAB. Practical implimintation. The obtained data allow to bring the model as close as possible to the real control system and to perform effective testing of its functioning in non-production conditions.

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Lin, Feng, and Wei Sun. "Warping Analysis in Laminated Object Manufacturing Process." Journal of Manufacturing Science and Engineering 123, no. 4 (May 1, 2001): 739–46. http://dx.doi.org/10.1115/1.1403447.

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This study presents an analysis of warping that occurs in the laminated object manufacturing process. Based on the study of thermal-mechanical behavior of the adhesive and its effect on the laminated materials, the cause of warping, the relationship between temperature and adhesive viscosity, and the adhesive connecting intensity is investigated. A heat transfer mathematical model and finite difference solution algorithm was developed to calculate the intralaminar thermal force induced by the material addition in the processing of laminated object manufacturing. The results of the model prediction were compared to available experimental data. Simulation of intralaminar thermal force and case studies show that the processing parameters, such as roller temperature, speed, and contact pressure, the mechanical properties of laminated material and adhesive will all contribute to the formability and warping of the laminated prototype. An optimal combination of the processing parameters may reduce the undesired warping effect.

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38

Saputra, Filmada Ocky, Ardiawan Bagus Harisa, and Zaenal Arifin. "Prototipe Pengaman Kebakaran Rumah Menggunakan Thermal Camera." Elektrika 13, no. 2 (November 4, 2021): 53. http://dx.doi.org/10.26623/elektrika.v13i2.4034.

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80% of cases of building or house fires in Indonesia are caused by electrical short circuits. Currently, there are only MCB and ELCB devices protecting for building electrical installations, but these devices cannot protect the conditions that cause fires. In a short circuit, there will be heating of the short cable or device. In this study, researchers used a thermal camera that can be placed on an electrical panel to be able monitor the temperature of electrical panel which includes cables, MCB, or can be placed on other devices. When the detected object temperature exceeds a predetermined limit, the device will provide a warning in the form of sound and text and can automatically cut off electricity in the building's electricity network. This research produces a prototype of a power grid safety device using a Raspberry Pi that can be applied to buildings and objects that have the potential to emit excess heat that can cause fires. Systems it will be able to monitor, provide warnings and can automatically cut off the electricity network when the temperature of the observed object exceeds the specified limit and has the potential to emit excess heat which can cause a fire.

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Pollacco, D. L., N. A. Walton, H. G. Schwarz, and S. A. Bell. "Sakurai's object: spectroscopic monitoring and nebula observations." Symposium - International Astronomical Union 180 (1997): 392. http://dx.doi.org/10.1017/s0074180900131547.

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Sakurai's object is thought to be undergoing a final thermal pulse or shell flash. It is the first example of this type of object to be studied using modern instrumentation and will be useful and unique for the time being for placing theoretical models of these transient events on a firm observational footing. The only other definite candidate is V605 Aql – now the WC central star of the planetary nebula Abell 58 – which is thought to have undergone a final thermal pulse around 1918.

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Mizginov, V. A., and S. Y. Danilov. "SYNTHETIC THERMAL BACKGROUND AND OBJECT TEXTURE GENERATION USING GEOMETRIC INFORMATION AND GAN." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W12 (May 9, 2019): 149–54. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w12-149-2019.

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<p><strong>Abstract.</strong> Nowadays methods based on deep neural networks show the best performance among image recognition and object detection algorithms. Nevertheless, such methods require to have large databases of multispectral images of various objects to achieve state-of-the-art results. Therefore the dataset generation is one of the major challenges for the successful training of a deep neural network. However, infrared image datasets that are large enough for successful training of a deep neural network are not available in the public domain. Generation of synthetic datasets using 3D models of various scenes is a time-consuming method that requires long computation time and is not very realistic. This paper is focused on the development of the method for thermal image synthesis using a GAN (generative adversarial network). The aim of the presented work is to expand and complement the existing datasets of real thermal images. Today, deep convolutional networks are increasingly used for the goal of synthesizing various images. Recently a new generation of such algorithms commonly called GAN has become a promising tool for synthesizing images of various spectral ranges. These networks show effective results for image-to-image translations. While it is possible to generate a thermal texture for a single object, generation of environment textures is extremely difficult due to the presence of a large number of objects with different emission sources. The proposed method is based on a joint approach that uses 3D modeling and deep learning. Synthesis of background textures and objects textures is performed using a generative-adversarial neural network and semantic and geometric information about objects generated using 3D modeling. The developed approach significantly improves the realism of the synthetic images, especially in terms of the quality of background textures.</p>

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41

Park, Chan Su, and Hi Seok Kim. "FPGA-based color enhancement algorithm for thermal object characterization." International Journal of Engineering & Technology 7, no. 3 (June 23, 2018): 1130. http://dx.doi.org/10.14419/ijet.v7i3.12557.

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Thermal imaging is used in numerous applications, especially in security, medical and other industry which requires a non-contact temperature measurement. This proposed algorithm improves the thermal image and makes more visible the separation of the sampled object from its background. The extracted image is produced by the following techniques: the pre-processing techniques are the combination of K-means clustering, and inverted Otsu method; canny edge detection and color mapping are used for highlighting the necessary characteristics of the sampled thermal image. The experimental results of this proposed algorithm show significant distinguishable features in terms of edge and color enhancement. It outperforms the other color correction method in terms of processing time, and the implementation reduced the resource utilization. Moreover, it minimizes the misclassified pixel in different noise variance. This work is synthesized with Xilinx Zync 7000 ZED ZC702.

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42

Klochko, V. K., and S. A. Smirnov. "Object tracking algorithm for a passive positioning system." Computer Optics 44, no. 2 (April 2020): 244–49. http://dx.doi.org/10.18287/2412-6179-co-609.

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We propose an algorithm for small-sized mobile object detection and trajectory parameter estimation for a passive positioning system that consists of several optical, thermal, and radio sensors. The algorithm is based on a combination of spatial and temporal processing of observation data. For spatial processing, a set of equations is solved that defines the sufficient condition for coupling the direction vectors to probable objects in the image stereo pair. Object coordinates and velocities for a single observation period are estimated. For temporal processing, the direction vectors are distributed based on connection to probable objects in a sequence of the capture intervals. The results of numerical modeling of the proposed algorithm show the advantage of combining the two approaches in comparison with the traditional object detection and tracking algorithms.

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43

Nancy, V., and G. Balakrishnan. "De-Noising Thermal Image Based On Haar Wavelet Transform Using Soft Threshold Technique." International Journal of Scientific & Engineering Research 12, no. 12 (December 25, 2021): 481–86. http://dx.doi.org/10.14299/ijser.2021.12.02.

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The concept of thermal imaging is inspiring the attention of many researchers, corporate companies and medical fields recently owing to its wide applications. The thermal camera captures the image of an object irrespective of the lighting condition. It can even picture the object in the dark environment, which is an added advantage. As a result, we can use the thermal image for object detection and classification process.

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44

Beaufait, Robert, Sebastian Ammann, and Ludger Fischer. "The Elephant Problem—Determining Bulk Thermal Diffusivity." Energies 14, no. 21 (November 8, 2021): 7444. http://dx.doi.org/10.3390/en14217444.

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This study investigates a measurement method of thermal diffusivity for samples with arbitrary geometries and unknown material properties. The aim is to curve fit the thermal diffusivity with the use of a numerical simulation and transient temperature measurement inside the object of interest. This approach is designed to assess bulk material properties of an object that has a composite material structure such as underground soil. The method creates the boundary conditions necessary to apply analytical theory found in the literature. It was found that measurements best correlated with theory and simulation at positions between the center and surface of an object.

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45

Bergamasco, Massimo, A. A. Alessi, and M. Calcara. "Thermal Feedback in Virtual Environments." Presence: Teleoperators and Virtual Environments 6, no. 6 (December 1997): 617–29. http://dx.doi.org/10.1162/pres.1997.6.6.617.

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This work refers to the study of thermal contact phenomena modeling for tactile feedback in virtual environments applications. The results of the modeling aspects for thermal replication are collected in specific functions that are used by the renderer of a virtual application. The finger temperature distribution versus time and contacted object temperature are the fundamental ways to approach, according to a specific modeling technique, the computation of the contact temperature occurring at the interface between the virtual hand and virtual object. Finger temperature distribution is then used for the control of thermal effectors. The modeling of the spatial and temporal distribution of the temperature in the human finger, when contact occurs with an external object at a defined temperature, is carried out in two phases: (a) determination of the temperature distribution in the finger when no contact is detected; and (b) determination of the temperature distribution in the finger when contact is detected. Results of the modeling are given and a procedure describing how these results can be used in the framework of a real application is presented.

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46

Akbari Sekehravani, Ehsan, Eduard Babulak, and Mehdi Masoodi. "Flying object tracking and classification of military versus nonmilitary aircraft." Bulletin of Electrical Engineering and Informatics 9, no. 4 (August 1, 2020): 1394–403. http://dx.doi.org/10.11591/eei.v9i4.1843.

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Tracking of moving objects in a sequence of images is one of the important and functional branches of machine vision technology. Detection and tracking of a flying object with unknown features are important issues in detecting and tracking objects. This paper consists of two basic parts. The first part involves tracking multiple flying objects. At first, flying objects are detected and tracked, using the particle filter algorithm. The second part is to classify tracked objects (military or nonmilitary), based on four criteria; Size (center of mass) of objects, object speed vector, the direction of motion of objects, and thermal imagery identifies the type of tracked flying objects. To demonstrate the efficiency and the strength of the algorithm and the above system, several scenarios in different videos have been investigated that include challenges such as the number of objects (aircraft), different paths, the diverse directions of motion, different speeds and various objects. One of the most important challenges is the speed of processing and the angle of imaging.

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47

Weinmann, M., J. Leitloff, L. Hoegner, B. Jutzi, U. Stilla, and S. Hinz. "Thermal 3D mapping for object detection in dynamic scenes." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-1 (November 7, 2014): 53–60. http://dx.doi.org/10.5194/isprsannals-ii-1-53-2014.

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The automatic analysis of 3D point clouds has become a crucial task in photogrammetry, remote sensing and computer vision. Whereas modern range cameras simultaneously provide both range and intensity images with high frame rates, other devices can be used to obtain further information which could be quite valuable for tasks such as object detection or scene interpretation. In particular thermal information offers many advantages, since people can easily be detected as heat sources in typical indoor or outdoor environments and, furthermore, a variety of concealed objects such as heating pipes as well as structural properties such as defects in isolation may be observed. In this paper, we focus on thermal 3D mapping which allows to observe the evolution of a dynamic 3D scene over time. We present a fully automatic methodology consisting of four successive steps: (i) a radiometric correction, (ii) a geometric calibration, (iii) a robust approach for detecting reliable feature correspondences and (iv) a co-registration of 3D point cloud data and thermal information via a RANSAC-based EPnP scheme. For an indoor scene, we demonstrate that our methodology outperforms other recent approaches in terms of both accuracy and applicability. We additionally show that efficient straightforward techniques allow a categorization according to background, people, passive scene manipulation and active scene manipulation.

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48

Liu, Qiao, Xiaohuan Lu, Zhenyu He, Chunkai Zhang, and Wen-Sheng Chen. "Deep convolutional neural networks for thermal infrared object tracking." Knowledge-Based Systems 134 (October 2017): 189–98. http://dx.doi.org/10.1016/j.knosys.2017.07.032.

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49

Skvortsov, B. V., A. S. Pertsovich, and D. M. Zhivonosnovskaya. "Simulation modeling of the signature of a thermal object." Journal of Optical Technology 85, no. 4 (April 1, 2018): 211. http://dx.doi.org/10.1364/jot.85.000211.

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50

Zhang, X.-L., E. Ball, C. Granier, L. Kochmanski, and S. D. Howe. "Near-Earth Object Interception Using Nuclear Thermal Rocket Propulsion." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 225, no. 2 (August 11, 2010): 181–93. http://dx.doi.org/10.1243/09544100jaero753.

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