Journal articles on the topic 'Quadrilateral detection'
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Gao, Pingping, and Yabin Gao. "Quadrilateral Interval Type-2 Fuzzy Regression Analysis for Data Outlier Detection." Mathematical Problems in Engineering 2019 (August 21, 2019): 1–9. http://dx.doi.org/10.1155/2019/4914593.
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This paper presents a fuzzy regression analysis method based on a general quadrilateral interval type-2 fuzzy numbers, regarding the data outlier detection. The Euclidean distance for the general quadrilateral interval type-2 fuzzy numbers is provided. In the sense of Euclidean distance, some parameter estimation laws of the type-2 fuzzy linear regression model are designed. Then, the data outlier detection-oriented parameter estimation method is proposed using the data deletion-based type-2 fuzzy regression model. Moreover, based on the fuzzy regression model, by using the root mean squared error method, an impact evaluation rule is designed for detecting data outlier. An example is finally provided to validate the presented methods.
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Wang, Mei, Zuo Peng Wang, and Yong Ling Chu. "Quadrilateral Extraction Method and its Application on Parking Cell Detection." Applied Mechanics and Materials 263-266 (December 2012): 2534–37. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.2534.
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This paper presents a quadrilate extraction method based on four vertices of the image object to solve the problrm of object area inaccuracy depending on conventional rectangular segmentation method. Firstly, four vertices are given by the mouse-click depending on quadilateral object spatial feature; and then the quadrilateral object shape feature is estimated by each side of the quadriangle computing by straight-line formulation of two adjacent vertices of object in order to acquare the quadrialeratal object inernal pixel. At last, the pixels of quadrialeratel external region are cleaned. Arbitrary quadrilateral region segmentation is achieved accurately. The method can be used for any quadrilateral region segmentation based on image processing, The experiments on actual color parking images show any parking cell template extraction accuracy reached 100% and parking cell state detection accuracy is 99.8%. The result verifies the algorithm effectiveness and robustnes
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Abu Hassan, Mohd Fadzil, Mohamad Hanif Md Saad, Mohd Faisal Ibrahim, and Aini Hussain. "A Finite State Machine Fall Detection Using Quadrilateral Shape Features." Bulletin of Electrical Engineering and Informatics 7, no. 3 (September 1, 2018): 359–66. http://dx.doi.org/10.11591/eei.v7i3.1184.
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A video-based fall detection system was presented; which consists of data acquisition, image processing, feature extraction, feature selection, classification and finite state machine. A two-dimensional human posture image was represented by 12 features extracted from the generalisation of a silhouette shape to a quadrilateral. The corresponding feature vectors for three groups of human pose were statistically analysed by using a non-parametric Kruskal Wallis test to assess the different significance level between them. From the statistical test, non-significant features were discarded. Four selected kernel-based Support Vector Machine: linear, quadratics, cubic and Radial Basis Function classifiers were trained to classify three human posture groups. Among four classifiers, the last one performed the best in terms of performance matric on testing set. The classifier outperformed others with high achievement ofaverage sensitivity, precision and F-score of 99.19%, 99.25% and 99.22%, respectively. Such pose classification model output was further used in a simple finite state machine to trigger the falling event alarms. The fall detection system was tested on different fall video sets and able to detect the presence offalling events in a frame sequence of videos with accuracy of 97.32% and low computional time.
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Patel, Ujjaval J., Nilesh G. Chothani, and Praghnesh J. Bhatt. "Adaptive quadrilateral distance relaying scheme for fault impedance compensation." Electrical, Control and Communication Engineering 14, no. 1 (July 1, 2018): 58–70. http://dx.doi.org/10.2478/ecce-2018-0007.
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Abstract Impedance reach of numerical distance relay is severely affected by Fault Resistance (RF), Fault Inception Angle (FIA), Fault Type (FT), Fault Location (FL), Power Flow Angle (PFA) and series compensation in transmission line. This paper presents a novel standalone adaptive distance protection algorithm for detection, classification and location of fault in presence of variable fault resistance. It is based on adaptive slope tracking method to detect and classify the fault in combination with modified Fourier filter algorithm for locating the fault. To realize the effectiveness of the proposed technique, simulations are performed in PSCAD using multiple run facility & validation is carried out in MATLAB® considering wide variation in power system disturbances. Due to adaptive setting of quadrilateral characteristics in accordance with variation in fault impedance, the proposed technique is 100 % accurate for detection & classification of faults with error in fault location estimation to be within 1 %. Moreover, the proposed technique provides significant improvement in response time and estimation of fault location as compared to existing distance relaying algorithms, which are the key attributes of multi-functional numerical relay
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Keserwani, Prateek, Ankit Dhankhar, Rajkumar Saini, and Partha Pratim Roy. "Quadbox: Quadrilateral Bounding Box Based Scene Text Detection Using Vector Regression." IEEE Access 9 (2021): 36802–18. http://dx.doi.org/10.1109/access.2021.3063030.
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Liu, Zhaoting, Longqing Zou, Xianglou Liu, Jiale Qiao, and Xiangbin Meng. "A point sound source location and detection method based on 19-element hemispheric distributed acoustic pressure sensor array." Insight - Non-Destructive Testing and Condition Monitoring 63, no. 8 (August 1, 2021): 479–87. http://dx.doi.org/10.1784/insi.2021.63.8.479.
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To solve the key problem of diagnosing the operating condition of an oil transfer pump unit in a 3D closed space, this paper presents an approach for a point sound source location and detection method based on a hemispheric distributed sound pressure sensor array. The array model consists of 19 sound pressure sensors acting in the radial direction and uniformly distributed over the hemispherical surface. A spatial rectangular coordinate system is established by taking the projection point of the central sensor arranged at the apex of the hemisphere to the ground as the origin of the spatial coordinates. With reference to the central sensor, the point sound source is located by selecting the maximum measured sound level and its spatial coordinate in each of the three layers of sensors surrounding it as parameters and using a triangular or a quadrilateral area location algorithm based on virtual instrument technology. According to the location of the source, the A-weighted sound level of the sound source point is derived by the inversion of the sound field distribution law. Results show that the triangular and quadrilateral area location algorithms are both effective. The errors in location become larger for a measured sound source far from the centre.
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Chen, YongQiang, Kai Luo, Liang Chen, Haobo Weng, and Wei Liang. "Application of edge detection based on hexagonal image structure to delamination detection of carbon fiber reinforced polymer material." Smart Materials and Structures 31, no. 4 (February 23, 2022): 045006. http://dx.doi.org/10.1088/1361-665x/ac5455.
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Abstract Delamination is one of the most critical damage modes in carbon fiber reinforced polymer (CFRP) materials, and is invisible to the naked eye. Although delamination defect images of CFRP materials can be obtained through ultrasonic tomography, it is still difficult to accurately identify the position and contours of defect images. In this study, four different delamination defect images of CFRP composite plates were obtained through a finite element simulation and fan-beam ultrasonic tomography. A hexagon algorithm based on interpolation is proposed that transforms the reconstructed defect images from square pixels into hexagonal pixels. The interpolation algorithm is based on the overlap between the square and hexagonal pixels. As the experiment results verify, the use of the hexagonal structure-based morphological method for edge detection significantly reduces the recognition error from 7.74% to 0.148% in comparison with a traditional quadrilateral structure. The experimental results also showed that this method can effectively reduce the artifact interference and obtain complete and accurate target edge information more effectively than a square structure.
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Zhao, Wen Dong, Hui Qi, and Hai Yan Zhou. "Segmentation Algorithm of Traffic Prohibited Area Based on Wavelet." Advanced Materials Research 542-543 (June 2012): 1316–19. http://dx.doi.org/10.4028/www.scientific.net/amr.542-543.1316.
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The status of transportation industry development of China has shown the necessity and urgency of the development of intelligent transportation systems. This article proposed a segmentation algorithm of traffic prohibited region based on wavelet transform. Based on the de-noising and image enhancement, sharpening pretreatment of the traffic video image captured on real-time, the algorithm combines the method determining the quadrilateral based on the sample images manually with the image segmentation based on wavelet transform in order to get the segmentation of traffic prohibited region which will be used in the detection of vehicle pressing highway central line region. The experimental results show that in the algorithm not only meet the real-time requirement of foundations but also improves the successful rate of detection results.
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Zhao, Fan, Sidi Shao, Lin Zhang, and Zhiquan Wen. "A Straightforward and Efficient Instance-Aware Curved Text Detector." Sensors 21, no. 6 (March 10, 2021): 1945. http://dx.doi.org/10.3390/s21061945.
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A challenging aspect of scene text detection is to handle curved texts. In order to avoid the tedious manual annotations for training curve text detector, and to overcome the limitation of regression-based text detectors to irregular text, we introduce straightforward and efficient instance-aware curved scene text detector, namely, look more than twice (LOMT), which makes the regression-based text detection results gradually change from loosely bounded box to compact polygon. LOMT mainly composes of curve text shape approximation module and component merging network. The shape approximation module uses a particle swarm optimization-based text shape approximation method (called PSO-TSA) to fine-tune the quadrilateral text detection results to fit the curved text. The component merging network merges incomplete text sub-parts of text instances into more complete polygon through instance awareness, called ICMN. Experiments on five text datasets demonstrate that our method not only achieves excellent performance but also has relatively high speed. Ablation experiments show that PSO-TSA can solve the text’s shape optimization problem efficiently, and ICMN has a satisfactory merger effect.
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Li, Shuangshuang, and Wenming Cao. "SEMPANet: A Modified Path Aggregation Network with Squeeze-Excitation for Scene Text Detection." Sensors 21, no. 8 (April 9, 2021): 2657. http://dx.doi.org/10.3390/s21082657.
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Recently, various object detection frameworks have been applied to text detection tasks and have achieved good performance in the final detection. With the further expansion of text detection application scenarios, the research value of text detection topics has gradually increased. Text detection in natural scenes is more challenging for horizontal text based on a quadrilateral detection box and for curved text of any shape. Most networks have a good effect on the balancing of target samples in text detection, but it is challenging to deal with small targets and solve extremely unbalanced data. We continued to use PSENet to deal with such problems in this work. On the other hand, we studied the problem that most of the existing scene text detection methods use ResNet and FPN as the backbone of feature extraction, and improved the ResNet and FPN network parts of PSENet to make it more conducive to the combination of feature extraction in the early stage. A SEMPANet framework without an anchor and in one stage is proposed to implement a lightweight model, which is embodied in the training time of about 24 h. Finally, we selected the two most representative datasets for oriented text and curved text to conduct experiments. On ICDAR2015, the improved network’s latest results further verify its effectiveness; it reached 1.01% in F-measure compared with PSENet-1s. On CTW1500, the improved network performed better than the original network on average.
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Hassan, Ehtesham, and Lekshmi V. L. "Scene Text Detection Using Attention with Depthwise Separable Convolutions." Applied Sciences 12, no. 13 (June 24, 2022): 6425. http://dx.doi.org/10.3390/app12136425.
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In spite of significant research efforts, the existing scene text detection methods fall short of the challenges and requirements posed in real-life applications. In natural scenes, text segments exhibit a wide range of shape complexities, scale, and font property variations, and they appear mostly incidental. Furthermore, the computational requirement of the detector is an important factor for real-time operation. To address the aforementioned issues, the paper presents a novel scene text detector using a deep convolutional network which efficiently detects arbitrary oriented and complex-shaped text segments from natural scenes and predicts quadrilateral bounding boxes around text segments. The proposed network is designed in a U-shape architecture with the careful incorporation of skip connections to capture complex text attributes at multiple scales. For addressing the computational requirement of the input processing, the proposed scene text detector uses the MobileNet model as the backbone that is designed on depthwise separable convolutions. The network design is integrated with text attention blocks to enhance the learning ability of our detector, where the attention blocks are based on efficient channel attention. The network is trained in a multi-objective formulation supported by a novel text-aware non-maximal procedure to generate final text bounding box predictions. On extensive evaluations on ICDAR2013, ICDAR2015, MSRA-TD500, and COCOText datasets, the paper reports detection F-scores of 0.910, 0.879, 0.830, and 0.617, respectively.
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Subrahmanyam, MSLB, V. Vijaya Kumar, and B. Eswara Reddy. "A New Algorithm for Skew Detection of Telugu Language Document based on Principle-axis Farthest Pairs Quadrilateral (PFPQ)." International Journal of Image, Graphics and Signal Processing 10, no. 3 (March 8, 2018): 47–58. http://dx.doi.org/10.5815/ijigsp.2018.03.06.
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Rucka, M., W. Witkowski, J. Chróscielewski, and K. Wilde. "Damage Detection of A T-Shaped Panel by Wave Propagation Analysis in the Plane Stress / Wykrywanie Uszkodzen W Tarczy Typu T Z Uzyciem Analizy Propagacji Fal W Płaskim Stanie Naprezenia." Archives of Civil Engineering 58, no. 1 (March 1, 2012): 3–24. http://dx.doi.org/10.2478/v.10169-012-0001-4.
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Abstract A computational approach to analysis of wave propagation in plane stress problems is presented. The initial-boundary value problem is spatially approximated by the multi-node C0 displacement-based isoparametric quadrilateral finite elements. To integrate the element matrices the multi-node Gauss-Legendre-Lobatto quadrature rule is employed. The temporal discretization is carried out by the Newmark type algorithm reformulated to accommodate the structure of local element matrices. Numerical simulations are conducted for a T-shaped steel panel for different cases of initial excitation. For diagnostic purposes, the uniformly distributed loads subjected to an edge of the T-joint are found to be the most appropriate for design of ultrasonic devices for monitoring the structural element integrity
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Wang, Jinghao, Xichao Teng, Zhang Li, Qifeng Yu, Yijie Bian, and Jiaqi Wei. "VSAI: A Multi-View Dataset for Vehicle Detection in Complex Scenarios Using Aerial Images." Drones 6, no. 7 (June 27, 2022): 161. http://dx.doi.org/10.3390/drones6070161.
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Arbitrary-oriented vehicle detection via aerial imagery is essential in remote sensing and computer vision, with various applications in traffic management, disaster monitoring, smart cities, etc. In the last decade, we have seen notable progress in object detection in natural imagery; however, such development has been sluggish for airborne imagery, not only due to large-scale variations and various spins/appearances of instances but also due to the scarcity of the high-quality aerial datasets, which could reflect the complexities and challenges of real-world scenarios. To address this and to improve object detection research in remote sensing, we collected high-resolution images using different drone platforms spanning a large geographic area and introduced a multi-view dataset for vehicle detection in complex scenarios using aerial images (VSAI), featuring arbitrary-oriented views in aerial imagery, consisting of different types of complex real-world scenes. The imagery in our dataset was captured with a wide variety of camera angles, flight heights, times, weather conditions, and illuminations. VSAI contained 49,712 vehicle instances annotated with oriented bounding boxes and arbitrary quadrilateral bounding boxes (47,519 small vehicles and 2193 large vehicles); we also annotated the occlusion rate of the objects to further increase the generalization abilities of object detection networks. We conducted experiments to verify several state-of-the-art algorithms in vehicle detection on VSAI to form a baseline. As per our results, the VSAI dataset largely shows the complexity of the real world and poses significant challenges to existing object detection algorithms. The dataset is publicly available.
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El-Sayed, Amr M., Nur Azah Hamzaid, Kenneth Y. S. Tan, and Noor Azuan Abu Osman. "Detection of Prosthetic Knee Movement Phases via In-Socket Sensors: A Feasibility Study." Scientific World Journal 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/923286.
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This paper presents an approach of identifying prosthetic knee movements through pattern recognition of mechanical responses at the internal socket’s wall. A quadrilateral double socket was custom made and instrumented with two force sensing resistors (FSR) attached to specific anterior and posterior sites of the socket’s wall. A second setup was established by attaching three piezoelectric sensors at the anterior distal, anterior proximal, and posterior sites. Gait cycle and locomotion movements such as stair ascent and sit to stand were adopted to characterize the validity of the technique. FSR and piezoelectric outputs were measured with reference to the knee angle during each phase. Piezoelectric sensors could identify the movement of midswing and terminal swing, pre-full standing, pull-up at gait, sit to stand, and stair ascent. In contrast, FSR could estimate the gait cycle stance and swing phases and identify the pre-full standing at sit to stand. FSR showed less variation during sit to stand and stair ascent to sensitively represent the different movement states. The study highlighted the capacity of using in-socket sensors for knee movement identification. In addition, it validated the efficacy of the system and warrants further investigation with more amputee subjects and different sockets types.
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Le, K. H., and P. H. Vu. "Effect Evaluation of Fault Resistance on the Operating Behavior of a Distance Relay." Engineering, Technology & Applied Science Research 8, no. 3 (June 19, 2018): 2975–80. http://dx.doi.org/10.48084/etasr.2051.
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This paper presents an application of a certain distance protection relay with a quadrilateral characteristic approach for the protection of the 110kV Duy Xuyen - Thang Binh transmission line in Vietnam using measured data from one terminal line. We propose the building process of a Matlab Simulink model for this relay that combines fault detection and classification block, apparent impedance calculation block for all types of faults and a trip logic block of three zone protection coordination. The proposed relay model is further tested using various fault scenarios on the transmission line. It is important to assess what happened, the actual conditions, the causes of mal-operation etc. Detailed explanation and results indicate that the proposed model behavior will help users to perform tests which correctly simulate real-world conditions besides that it properly interprets test results and troubleshoot distance function problems when results are not as expected.
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MATI, Ayache, Baadji BOUSAADIA, and Hamid BENTARZI. "A New Model of Numerical MHO Distance Relay Associated with Power Swing Detector." Algerian Journal of Signals and Systems 1, no. 2 (February 2, 2021): 121–28. http://dx.doi.org/10.51485/ajss.v1i2.26.
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In conventional transmission line protection, a distance relay is used to provide the primary as well as backup protection. The voltage and current phasors measurement needed by the distance relay for determining the impedance may be affected by the power disturbances such as power swing. Consequently, this power swing may cause mal-operation of Zone three distance relays which in turn may affect on the reliability of the whole protective scheme. Many power swing blocking functions (PSB) have been developed to mitigate these effects. In this paper, a new model of Mho distance relay with dual-quadrilateral power swing detection characteristic has been developed and implemented first in PC using LabVIEW, then tested using Power System Simulink Model under different faults and power swing conditions. Finally, the relay prototype has been realized using acquisition card NI USB-6009, which acquires real-time signals of the currents and the voltages, processes them digitally and outputs tripping or blocking signal to the circuit breaker. The obtained results show that the relay provides good discrimination between a fault and power swing condition.
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Mochizuki, T., H. Isoda, T. Masui, Y. Ohkawa, M. Takahashi, Y. Takehara, K. Ichijo, N. Kodaira, and H. Kitanaka. "Occlusion of the posterior humeral circumflex artery: detection with MR angiography in healthy volunteers and in a patient with quadrilateral space syndrome." American Journal of Roentgenology 163, no. 3 (September 1994): 625–27. http://dx.doi.org/10.2214/ajr.163.3.8079857.
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Yang, Fei, Honghao Yue, Meng Li, Jianguo Tao, and Zongquan Deng. "Research on folding suspension of multi-constrained rover based on the variation and fusion of rods and pairs." International Journal of Advanced Robotic Systems 14, no. 4 (July 1, 2017): 172988141772733. http://dx.doi.org/10.1177/1729881417727336.
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Planetary rovers with folding functions can solve the contradiction between the limited space of the vehicle and the functional diversity of the rover and greatly improve the efficiency–cost ratio of space launch activities. In this article, the multi-constrained quadrilateral suspension is considered based on the practical requirements of planetary detection. Based on graph theory and metamorphic theory, the structural characteristics and movement patterns of the rover are analyzed, the configuration transforming process of adding or decreasing the number of rods and kinematic pairs during folding is studied, and the corresponding mathematical model is established. The suspension of the rover is divided into three basic units, and the folding study is performed around each unit. The folding set of each unit type is given, and a feasible folding set is selected for each type of unit according to their structural characteristics and constraint conditions. At the same time, 15-folding schemes for the rover are given, and the optimal scheme is determined. According to the final folding scheme of the rover, the principle prototype of the rover is developed, and the functional experiment of the folding and unfolding is performed. The experimental results verify the feasibility and rationality of the folding scheme, indicating that the developed detection vehicle has a large fold ratio, which can fully adapt to the limited space inside the rocket. The theoretical and technical results can provide technical support for the engineering application of subsequent rovers with folding.
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Xing, Wang, Xu, Lin, Li, Jiao, Zhang, and Liu. "A Depth-Adaptive Waveform Decomposition Method for Airborne LiDAR Bathymetry." Sensors 19, no. 23 (November 20, 2019): 5065. http://dx.doi.org/10.3390/s19235065.
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Airborne LiDAR bathymetry (ALB) has shown great potential in shallow water and coastal mapping. However, due to the variability of the waveforms, it is hard to detect the signals from the received waveforms with a single algorithm. This study proposed a depth-adaptive waveform decomposition method to fit the waveforms of different depths with different models. In the proposed method, waveforms are divided into two categories based on the water depth, labeled as “shallow water (SW)” and “deep water (DW)”. An empirical waveform model (EW) based on the calibration waveform is constructed for SW waveform decomposition which is more suitable than classical models, and an exponential function with second-order polynomial model (EFSP) is proposed for DW waveform decomposition which performs better than the quadrilateral model. In solving the model’s parameters, a trust region algorithm is introduced to improve the probability of convergence. The proposed method is tested on two field datasets and two simulated datasets to assess the accuracy of the water surface detected in the shallow water and water bottom detected in the deep water. The experimental results show that, compared with the traditional methods, the proposed method performs best, with a high signal detection rate (99.11% in shallow water and 74.64% in deep water), low RMSE (0.09 m for water surface and 0.11 m for water bottom) and wide bathymetric range (0.22 m to 40.49 m).
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Abdollahzadeh, Mohammad Amin, Adnan Kefal, and Mehmet Yildiz. "A Comparative and Review Study on Shape and Stress Sensing of Flat/Curved Shell Geometries Using C0-Continuous Family of iFEM Elements." Sensors 20, no. 14 (July 8, 2020): 3808. http://dx.doi.org/10.3390/s20143808.
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In this study, we methodologically compare and review the accuracy and performance of C0-continuous flat and curved inverse-shell elements (i.e., iMIN3, iQS4, and iCS8) for inverse finite element method (iFEM) in terms of shape, strain, and stress monitoring, and damage detection on various plane and curved geometries subjected to different loading and constraint conditions. For this purpose, four different benchmark problems are proposed, namely, a tapered plate, a quarter of a cylindrical shell, a stiffened curved plate, and a curved plate with a degraded material region in stiffness, representing a damage. The complexity of these test cases is increased systematically to reveal the advantages and shortcomings of the elements under different sensor density deployments. The reference displacement solutions and strain-sensor data used in the benchmark problems are established numerically, utilizing direct finite element analysis. After performing shape-, strain-, and stress-sensing analyses, the reference solutions are compared to the reconstructed solutions of iMIN3, iQS4, and iCS8 models. For plane geometries with sparse sensor configurations, these three elements provide rather close reconstructed-displacement fields with slightly more accurate stress sensing using iCS8 than when using iMIN3/iQS4. It is demonstrated on the curved geometry that the cross-diagonal meshing of a quadrilateral element pattern (e.g., leading to four iMIN3 elements) improves the accuracy of the displacement reconstruction as compared to a single-diagonal meshing strategy (e.g., two iMIN3 elements in a quad-shape element) utilizing iMIN3 element. Nevertheless, regardless of any geometry, sensor density, and meshing strategy, iQS4 has better shape and stress-sensing than iMIN3. As the complexity of the problem is elevated, the predictive capabilities of iCS8 element become obviously superior to that of flat inverse-shell elements (e.g., iMIN3 and iQS4) in terms of both shape sensing and damage detection. Comprehensively speaking, we envisage that the set of scrupulously selected test cases proposed herein can be reliable benchmarks for testing/validating/comparing for the features of newly developed inverse elements.
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Maiwald, F., D. Schneider, F. Henze, S. Münster, and F. Niebling. "FEATURE MATCHING OF HISTORICAL IMAGES BASED ON GEOMETRY OF QUADRILATERALS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2 (May 30, 2018): 643–50. http://dx.doi.org/10.5194/isprs-archives-xlii-2-643-2018.
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This contribution shows an approach to match historical images from the photo library of the Saxon State and University Library Dresden (SLUB) in the context of a historical three-dimensional city model of Dresden. In comparison to recent images, historical photography provides diverse factors which make an automatical image analysis (feature detection, feature matching and relative orientation of images) difficult. Due to e.g. film grain, dust particles or the digitalization process, historical images are often covered by noise interfering with the image signal needed for a robust feature matching. The presented approach uses quadrilaterals in image space as these are commonly available in man-made structures and façade images (windows, stones, claddings). It is explained how to generally detect quadrilaterals in images. Consequently, the properties of the quadrilaterals as well as the relationship to neighbouring quadrilaterals are used for the description and matching of feature points. The results show that most of the matches are robust and correct but still small in numbers.
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Golovin, Oleksandr. "Recognition of Geometric Figures and Determination of Their Characteristics by Means of Computer Vision." Cybernetics and Computer Technologies, no. 1 (June 30, 2022): 49–63. http://dx.doi.org/10.34229/2707-451x.22.1.6.
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Introduction. Many computer vision applications often use procedures for recognizing various shapes and estimating their dimensional characteristics. The entire pipeline of such processing consists of several stages, each of which has no clearly defined boundaries. However, it can be divided into low, medium, and high-level processes. Low-level processes only deal with primitive operations such as preprocessing to reduce noise, enhance contrast, or sharpen images. The processes of this level are characterized by the fact that there are images at the input and output. Image processing at the middle level covers tasks such as segmentation, description of objects, and their compression into a form convenient for computer processing. Middle-level processes are characterized by the presence of images only at the input, and only signs and attributes extracted from images are received at the output. High-level processing involves “understanding” a set of recognized objects and recognizing their interactions. Using the example of the developed software models for recognizing figures and estimating their characteristics, it is shown that the image processing process is reduced to transforming spatial image data into metadata, compressing the amount of information, which leads to a significant increase in the importance of data. This indicates that at the input of the middle level, the image should be as informative as possible (with high contrast, no noise, artifacts, etc.) because after the transformation of the spatial image data into metadata, no further the procedures are not able to correct the data obtained by the video sensors in the direction of improving or increasing the information content. Recognition of figures in an image can be realized quite efficiently through the use of the procedure for determining the contours of figures. To do this, you need to determine the boundaries of objects and localize them in the image, often the first step for procedures such as separating objects from the background, image segmentation, detection and recognition of various objects, etc. The purpose of the article is to study the image processing pipeline from the moment of image fixation to the recognition of a certain set of figures (for example, geometric shapes, such as a triangle, quadrilateral, etc.) in an image, the development of software models for recognizing figures in an image, determining the center of mass figures by means of computer vision. Results. We proposed and tested some variants of nonlinear estimating problem. The properties of such problems depend on value of regulating parameter. The dependence of estimation on value of parameter was studied. It was defined a range for parameter's value for which estimating problem gives adequate result for initial task. Numerical examples show how much volume of calculations reduces when using a dynamic branching tree. Conclusions. The results obtained can be used in many applications of computer vision, for example, counting objects in a scene, estimating their parameters, estimating the distance between objects in a scene, etc. Keywords: contour, segmentation, image binarization, computer vision, histogram.
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Sablé-Meyer, Mathias, Joël Fagot, Serge Caparos, Timo van Kerkoerle, Marie Amalric, and Stanislas Dehaene. "Sensitivity to geometric shape regularity in humans and baboons: A putative signature of human singularity." Proceedings of the National Academy of Sciences 118, no. 16 (April 12, 2021): e2023123118. http://dx.doi.org/10.1073/pnas.2023123118.
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Among primates, humans are special in their ability to create and manipulate highly elaborate structures of language, mathematics, and music. Here we show that this sensitivity to abstract structure is already present in a much simpler domain: the visual perception of regular geometric shapes such as squares, rectangles, and parallelograms. We asked human subjects to detect an intruder shape among six quadrilaterals. Although the intruder was always defined by an identical amount of displacement of a single vertex, the results revealed a geometric regularity effect: detection was considerably easier when either the base shape or the intruder was a regular figure comprising right angles, parallelism, or symmetry rather than a more irregular shape. This effect was replicated in several tasks and in all human populations tested, including uneducated Himba adults and French kindergartners. Baboons, however, showed no such geometric regularity effect, even after extensive training. Baboon behavior was captured by convolutional neural networks (CNNs), but neither CNNs nor a variational autoencoder captured the human geometric regularity effect. However, a symbolic model, based on exact properties of Euclidean geometry, closely fitted human behavior. Our results indicate that the human propensity for symbolic abstraction permeates even elementary shape perception. They suggest a putative signature of human singularity and provide a challenge for nonsymbolic models of human shape perception.
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Chen, YongQiang, kai luo, Liang Chen, HaoBo Weng, and Wei Liang. "Application of Edge Detection Based on Hexagonal Image Structure to Delamination Detection of Carbon Fiber Reinforced Polymer Material." Smart Materials and Structures, February 9, 2022. http://dx.doi.org/10.1088/1361-665x/ac5335.
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Abstract Delamination is one of the most critical damage modes in carbon fiber reinforced polymer materials, and is invisible to the naked eye. Although delamination defect images of carbon fiber reinforced polymer materials can be obtained through ultrasonic tomography, it is still difficult to accurately identify the position and contours of defect images. In this study, four different delamination defect images of carbon fiber reinforced polymer composite plates were obtained through a finite element simulation and fan-beam ultrasonic tomography. A hexagon algorithm based on interpolation is proposed that transforms the reconstructed defect images from square pixels into hexagonal pixels. The interpolation algorithm is based on the overlap between the square and hexagonal pixels. As the experiment results verify, the use of the hexagonal structure-based morphological method for edge detection significantly reduces the recognition error from 7.74% to 0.148% in comparison with a traditional quadrilateral structure. The experimental results also showed that this method can effectively reduce the artifact interference and obtain complete and accurate target edge information more effectively than a square structure.
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Wankhede, Pankaj, Tejas Radhakrishnan, Sudha Radhika, and Suresh Kurra. "Corner detection of a quadrilateral for strain analysis in sheet metal forming by image processing." Advances in Materials and Processing Technologies, January 26, 2021, 1–11. http://dx.doi.org/10.1080/2374068x.2021.1878710.
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Lochner, M., L. Rudnick, I. Heywood, K. Knowles, and S. S. Shabala. "A unique, ring-like radio source with quadrilateral structure detected with machine learning." Monthly Notices of the Royal Astronomical Society, January 11, 2023. http://dx.doi.org/10.1093/mnras/stad074.
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Abstract We report the discovery of a unique object in the MeerKAT Galaxy Cluster Legacy Survey (MGCLS) using the machine learning anomaly detection framework Astronomaly. This strange, ring-like source is 30′ from the MGCLS field centred on Abell 209, and is not readily explained by simple physical models. With an assumed host galaxy at redshift 0.55, the luminosity (1025 W Hz−1) is comparable to powerful radio galaxies. The source consists of a ring of emission 175 kpc across, quadrilateral enhanced brightness regions bearing resemblance to radio jets, two “ears” separated by 368 kpc, and a diffuse envelope. All of the structures appear spectrally steep, ranging from -1.0 to -1.5. The ring has high polarization (25%) except on the bright patches (<10%). We compare this source to the Odd Radio Circles recently discovered in ASKAP data and discuss several possible physical models, including a termination shock from starburst activity, an end-on radio galaxy, and a supermassive black hole merger event. No simple model can easily explain the observed structure of the source. This work, as well as other recent discoveries, demonstrates the power of unsupervised machine learning in mining large datasets for scientifically interesting sources.
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Casanova, Cesar F., A. Gallego, and M. Lázaro. "On the Accuracy of a Four-Node Delaminated Composite Plate Element and Its Application to Damage Detection." Journal of Vibration and Acoustics 135, no. 6 (June 19, 2013). http://dx.doi.org/10.1115/1.4023994.
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This paper presents a new four-node composite element, which incorporates nd delaminations through its thickness. Based on the extended finite element method (X-FEM) technology, the element is particularized on a CLT (classical laminate theory). Delamination is considered in the kinematic equations with additional degrees of freedom. The result is a four-node quadrilateral element requiring only two single FEM (finite element method) formulations, a bending one and a membrane one. An important result is that this formulation has the same accuracy as when separate elements are considered (“four region approach”). It is furthermore proven that the delaminated element passes the “patch test” if the selected FEM formulations to build the element pass the test in the pure single problems, making this methodology very attractive to develop other fractured elements. To illustrate this result, two benchmark problems were studied: first a complete delaminated cantilever plate, and second a complete delaminated circular plate. The element was tested in the context of SHM (structural health monitoring). Frequency shifts, damage indexes, and changes in mode shapes and frequency response functions (FRF) were obtained to quantify the severity of damage due to delamination.
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& AL – Bedrey, AL Kafage. "EXTENSION AGRICULTURAL INNOVATION FOR BEE KEEPERS TO DEVELOP AND INCREASE PRODUCTIVITY IN THE CENTRAL REGION OF IRAQ." IRAQI JOURNAL OF AGRICULTURAL SCIENCES 47, no. 5 (October 28, 2016). http://dx.doi.org/10.36103/ijas.v47i5.497.
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The research aimed to identify the level of bee keepers innovation to develop and increase productivity in the central region of Iraq , In order to achieve the goals of research a questionnaire consisted of two parts, designed the first part included a bilateral scale to measure the level of beekeepers innovations, consists of ( 46 ) paragraphs Distributed on five fields (bee keeping , the area to take advantage of the bees in environment, the detection of diseases and pests ,the treating diseases and pest control , the field of honey products and peripherals manufacturing ), The second part included a barometer quadrilateral to measure the reasons consists of ( 34 ) paragraphs Distributed on four pivots (environmental causes , extension, economic , social). The research community a random sample ( 38%)of the which is (Baghdad, Babil, Najaf) a random sample (15%) of the total number of beekeepers totaling (1098) breeders in the provinces covered by the research, to be the size of the sample (165) educator for the bees . The results showed that bee keepers suffer from weak innovation levels, as the highest rate is (66.7%) of the beekeepers within the level of innovation (0-15) and an average of (11.12) degree and a standard deviation (7.53) degrees . The results showed that the causes that lead bee keepers to innovation is (social causes) came first in the level of importance as it reached the level of significance (2.38) degrees while last (extension causes) and the level of significance (1.93) degrees Researcher recommends the necessity of providing the requirements and production equipment for beekeeping encouraging high international standard prices in order to promote the level of innovation to beekeepers in central region of Iraq and should be concerted efforts by government agencies and of devices guidance, research and beekeepers.