Relevant bibliographies by topics / Mean square Canny error

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Mean square Canny error'

Author: Grafiati
Published: 6 September 2023

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Journal articles on the topic "Mean square Canny error"

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Chhabra, Mohit, and Rajneesh Kumar. "Comparison of Different Edge Detection Techniques to Improve Quality of Medical Images." Journal of Computational and Theoretical Nanoscience 17, no. 6 (June 1, 2020): 2496–507. http://dx.doi.org/10.1166/jctn.2020.8921.

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In modern era the major challenge will betodetect diseases from Medical Images. To curb this challenge, different efficient image feature extraction techniques was required in medical fields. Today Medical field industry today deals with millions of images of different disease of brain heart, lungs. So in this paper, we had presented a comparison among different feature extraction technique like Canny, Laplacian of Gaussian, Sobel, Prewit on large number of images of lung disease. The objective of our research work was to find best extraction techniques based on various image quality parameters such as Mean absolute error (MAE), Root mean square error (RMSE), mean square error (MSE), Signal to noise ratio (SNR).
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Fendriani, Yoza, Regita Kharisma, and Mardian Peslinof. "ANALISIS PERBANDINGAN VARIASI FILTER PADA DETEKSI TEPI MENGGUNAKAN METODE CANNY TERHADAP CITRA CT-SCAN KANKER PARU-PARU." JOURNAL ONLINE OF PHYSICS 8, no. 2 (April 1, 2023): 77–81. http://dx.doi.org/10.22437/jop.v8i2.24451.

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Telah dilakukan penelitian deteksi tepi citra CT-Scan kanker paru-paru metode Canny menggunakan beberapa filter yaitu mean, median, dan Gaussian filter. Deteksi tepi ini bertujuan untuk mengetahui batasan dari kanker serta mengetahui filter terbaik dalam deteksi tepi metode Canny berdasarkan nilai Mean Square Error (MSE) dan Peak Signal Noise to Ratio (PSNR). Berdasarkan beberapa penelitian metode Canny adalah metode yang sangat baik dalam deteksi tepi citra karena menghasilkan bentuk tepi citra yang terlihat jelas, tetapi namun kualitas citra masih kurang baik karena banyaknya noise. Noise adalah citra atau pixel yang mengganggu kualitas citra maka dilakukan proses smooting dengan menggunakan filter. Terdapat enam citra pasien kanker paru-paru yang diuji dengan tahapan pendeteksian tepi pada metode Canny tanpa filter dan menggunakan filter. Dari hasil penelitian, filter median mendapatkan hasil yang lebih baik dari filter mean dan Gaussian. Berdasarkan nilai MSE dan PSNR filter median memiliki nilai yang lebih baik dari yang lainnya. Nilai MSE dari filter median yaitu 47 dan nilai PSNR filter median yaitu 31dB.
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Kieu, S. T. H., A. Bade, and M. H. A. Hijazi. "Modified canny edge detection technique for identifying endpoints." Journal of Physics: Conference Series 2314, no. 1 (August 1, 2022): 012023. http://dx.doi.org/10.1088/1742-6596/2314/1/012023.

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Abstract Edge detection is an image processing technique that retains the edges of an object in an image while discarding other features. The Canny edge detection technique is regarded as one of the most successful edge detection algorithms because of the good edge detection effect. However, one of its problems is the discontinued edges. In this paper, we present an endpoint identification algorithm that can pinpoint the position of the discontinued edges. After the endpoints are identified, they are paired together based on distance, and the broken gaps are filled by connecting the endpoints. Results have shown that, visually, our method has fewer discontinued edges when compared to Canny. Also, the mean square error of our method is lower than traditional Canny, indicating that our technique produces edge images that are more accurate than the traditional Canny.
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Sugandi, Budi, and Yuniatmi Syamsudin. "Deteksi Tepi Canny dan RMSE untuk Identifikasi Kerusakan pada Kemasan Minuman." JURNAL INTEGRASI 14, no. 2 (October 31, 2022): 110–13. http://dx.doi.org/10.30871/ji.v14i2.4420.

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Salah satu minuman kemasan yang banyak dipakai adalah kemasan kaleng. Kekurangan kemasan minuman kaleng adalah sifatnya yang mudah rusak akibat benturan dengan benda lain maupun terjatuh. Kemasan yang rusak mengakibatkan produk menjadi tidak sempurna. Sehingga proses identifikasi kerusakan kemasan kaleng menjadi sangat penting sebagai proses penjamin kualitas produk. Penelitian ini ditujukan sebagai salah satu solusi untuk mengidentifikasi kerusakan pada kemasan minuman kaleng. Metode deteksi yang diusulkan berdasarkan pada deteksi tepi Canny dan RMSE (Root Mean Square Error). Proses awal deteksi dimulai dengan pengkapturan citra kaleng oleh kamera. Citra asli RGB ini akan dikonversi ke citra biner untuk kemudian dilakukan deteksi tepi Canny. Pada penelitian ini, digunakan nilai high threshold 20 dan low threshold 10 pada proses deteksi tepi Canny. Citra hasil deteksi tepi Canny akan dibandingkan dengan citra deteksi Canny yang menjadi referensi menggunakan nilai RMSE. Nilai RMSE yang digunakan untuk kategori OK dan NG dibatasi pada nilai 70. Hasil pengujian menunjukan nilai RMSE untuk kategori OK berada pada rentang 70.72 dan 85.24 sedangkan kategori NG berada pada rentang 47.99 dan 69.93. Pengujian dilakukan menggunakan citra kaleng bagian atas dan tengah.
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Wang, Zhenyu, Mingshun Yang, Leijie Ren, Jiali Han, Yirou Liu, Xingbai Zhao, and Yangang Feng. "An Improved BM3D-Canny-Zernike Algorithm for Micro-Size Detection of Electronic Connectors." Traitement du Signal 39, no. 3 (June 30, 2022): 899–906. http://dx.doi.org/10.18280/ts.390315.

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To detect the micro-size injection molded parts of electronic connectors, this paper establishes a complete size detection system based on machine vision, and measures the size through image acquisition and processing, according to the features of the injection molded parts. The proposed system is called the improved BM3D-Canny-Zernike algorithm. Specifically, the traditional block matching and three-dimensional filtering (BM3D) image denoising algorithm was improved to optimize the peak signal-to-noise ratio (PSNR) and reduce the mean squared error (MSE). Then, the Canny algorithm was improved for pixel-level edge detection, and the Zernike moment is improved for detecting edges on the subpixel-level more effectively and reducing the calculation amount. Finally, the least squares method was employed to fit the edge to be measured. The exact pixel length was obtained by solving the function of different edges, thereby realizing size measurement. Experimental results show that the mean error percentage of our algorithm was 8.73%, which meets the needs of industrial detection.
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Kosukegawa, Hiroyuki, Yuta Kiso, Mitsuo Hashimoto, Tetsuya Uchimoto, and Toshiyuki Takagi. "Evaluation of detectability of differential type probe using directional eddy current for fibre waviness in CFRP." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 378, no. 2182 (September 14, 2020): 20190587. http://dx.doi.org/10.1098/rsta.2019.0587.

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This paper describes the detectability of eddy current testing (ECT) using directional eddy current for detection of in-plane fibre waviness in unidirectional carbon fibre reinforced plastic (CFRP) laminate. Three different types of probes, such as circular driving, symmetrical driving and uniform driving probe, were proposed, and the waviness angle was extracted from the contour map of the ECT signal by applying a Canny filter and a Hough transform. By comparing both the waviness angle estimated by ECT and that obtained by an X-ray CT image, the standard deviation (precision) and root mean square error (accuracy) were evaluated to discuss the detectability of these probes. The directional uniform driving probe shows the best detectability and can detect fibre waviness with a waviness angle of more than 2° in unidirectional CFRP. The probe shows a root mean square error of 1.90° and a standard deviation of 4.49° between the actual waviness angle and the angle estimated by ECT. This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.
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Lu, Ting, Beibei Zhang, Yunpeng Hu, and Jianyong Chen. "Computed Tomography Imaging Based on Edge Detection Algorithm in Diagnosis and Rehabilitation Nursing of Stroke Patients with Motor Dysfunction." Scientific Programming 2021 (October 27, 2021): 1–10. http://dx.doi.org/10.1155/2021/5499351.

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This study was to explore the effect of computed tomography (CT) images processed by image edge detection technology based on the improved Canny algorithm in the diagnosis of stroke patients with mobility dysfunction and to evaluate the clinical application value of early rehabilitation nursing (ERN). 114 patients who were diagnosed and treated in hospital and were suspected of having stroke movement dysfunction were selected as the research objects, and they were randomly divided into two groups, each with 57 patients. Patients in the control group were diagnosed with conventional CT examination, and the patients in observation group were diagnosed based on the CT images processed by the image edge detection technology based on the improved Canny algorithm. Patients in the observation group were divided into a group C and a group O. Patients (27 cases) in group O received rehabilitation training within 3 days after their vital signs were stabilized, and patients (30 cases) in group C received rehabilitation training within 3∼7 days after their condition was stabilized. The CT image diagnosis effects on patients of the control group and the observation group were analyzed, and the ERN effect on patients of the C group and the O group was compared. The results showed that the mean square error (MSE) of the improved Canny algorithm (233.78) was smaller than that of the traditional Canny algorithm and Sobel and Prewitt algorithm, and the peak signal-to-noise ratio (PSNR) (27.89) was greater than that of the traditional Canny algorithm and Sobel and Prewitt algorithm ( P < 0.05 ). Compared with the control group, the sensitivity (85.00% vs. 62.12%), specificity (70.59% vs. 36.36%), and accuracy (80.70% vs. 54.39%) of the examination method of the observation group were much higher ( P < 0.05 ). In addition, the total effective rate of patients in group O was 89.47%, which was greatly higher than that of group C (70.18%), and the scores of Meyer index and Barthel index were also higher in contrast to those of group C ( P < 0.05 ). In conclusion, the improved Canny algorithm showed a clearer display on the edge detection of CT images and good application effect. It showed the effect of making conventional CT more accurate in the examination and diagnosis of stroke patients, and it was worthy of clinical application and promotion. The research showed that the timelier rehabilitation training, the better the treatment effect of patients.
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Liu, Zhaoyang, Huajie Hong, Zihao Gan, Jianhua Wang, and Yaping Chen. "An Improved Method for Evaluating Image Sharpness Based on Edge Information." Applied Sciences 12, no. 13 (July 2, 2022): 6712. http://dx.doi.org/10.3390/app12136712.

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In order to improve the subjective and objective consistency of image sharpness evaluation while meeting the requirement of image content irrelevance, this paper proposes an improved sharpness evaluation method without a reference image. First, the positions of the edge points are obtained by a Canny edge detection algorithm based on the activation mechanism. Then, the edge direction detection algorithm based on the grayscale information of the eight neighboring pixels is used to acquire the edge direction of each edge point. Further, the edge width is solved to establish the histogram of edge width. Finally, according to the performance of three distance factors based on the histogram information, the type 3 distance factor is introduced into the weighted average edge width solving model to obtain the sharpness evaluation index. The image sharpness evaluation method proposed in this paper was tested on the LIVE database. The test results were as follows: the Pearson linear correlation coefficient (CC) was 0.9346, the root mean square error (RMSE) was 5.78, the mean absolute error (MAE) was 4.9383, the Spearman rank-order correlation coefficient (ROCC) was 0.9373, and the outlier rate (OR) as 0. In addition, through a comparative analysis with two other methods and a real shooting experiment, the superiority and effectiveness of the proposed method in performance were verified.
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Ledalla, Sukanya, Vijendar Reddy Gurram, Gopala Krishna P, Saiteja Vodnala, Maroof Md, and Raviteja Reddy Annapuredddy. "Density based smart traffic control system using canny edge detection algorithm along with object detection." E3S Web of Conferences 391 (2023): 01061. http://dx.doi.org/10.1051/e3sconf/202339101061.

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It is urgently necessary to combine current advancements to work on the cutting edge inrush hour jam the executives, as urban congestion is one of the world’s biggest concerns. Existing methodologies, for example, traffic police and traffic lights are neither fulfilling nor viable. Consequently, a traffic management system that utilizes sophisticated edge detection and digital image processing to measure vehicle density in real time is developed in this setting. Computerizedimage processing should be used to detect edges. To extract significant traffic data from CCTV images, the edge recognition method is required. The astute edge finder outperforms other processes in terms of accuracy, entropy, PSNR (peak signal to noise ratio), MSE (mean square error), and execution time. There are a number of possible edge recognition calculations. In terms of reaction time, vehicle the board, mechanization, dependability, and overall productivity, this framework performs significantly better than previous models. Utilizing a few model images of various traffic scenarios, appropriate schematics are also provided for a comprehensive approach that includes image collection, edge distinguishing evidence, and green sign classification. Also recommended is a system with object identification and priority for ambulances stuck in traffic.
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Yin, Hua, Jingling Xu, Yinglong Wang, Dianming Hu, and Wenlong Yi. "A Novel Method of Situ Measurement Algorithm for Oudemansiella raphanipies Caps Based on YOLO v4 and Distance Filtering." Agronomy 13, no. 1 (December 30, 2022): 134. http://dx.doi.org/10.3390/agronomy13010134.

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Oudemansiella raphanipies has gradually gained more and more popularity in the market for its delicious taste, while enhancing human immunity and regulating human body functions as well. To achieve the high-throughput and automatic monitoring of the phenotypes of Oudemansiella raphanipies, a novel method, based on YOLO v4 and Distance Filter (DF), was proposed for high-precision diameter estimation of Oudemansiella raphanipies caps. To begin with, a dataset of Oudemansiella raphanipies was established by the laboratory cultivation and collection of factory samples. The improved YOLO v4 target detection model with added CBAM modules to each convolution block in the backbone was trained to locate the caps and, thus, obtain an approximate bounding box. Secondly, the approximate contour of the cap was gained through the H component, canny edge detection operators, and distance filtering to conduct the noise elimination. Finally, the center of the fitted circle and its accurate contour of the cap could be obtained by the constrained least square method, and the diameter of the fitted circle was estimated by the calibration data. The results of practical tests showed that this method achieved an accuracy of 95.36% in recognizing Oudemansiella raphanipies caps in the growing bed, and the fitting effect of caps was superior to Circle Hough Transform (CHT), the least square method (LS), and Ransac, with no manual adjustment on parameters. Compared with the manual measurement, the mean absolute error (MAE) of this method was 0.77 mm, the coefficient of determination (R2) was 0.95, and the root mean square error (RMSE) was 0.96 mm. Therefore, the model had high-cost performance and could meet the needs of continuous and long-term tracking of the cap shape of Oudemansiella raphanipies, providing the basis for future high-throughput breeding and machine picking.
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Dissertations / Theses on the topic "Mean square Canny error"

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Degtyarena, Anna Semenovna. "The window least mean square error algorithm." CSUSB ScholarWorks, 2003. https://scholarworks.lib.csusb.edu/etd-project/2385.

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In order to improve the performance of LMS (least mean square) algorithm by decreasing the amount of calculations this research proposes to make an update on each step only for those elements from the input data set, that fall within a small window W near the separating hyperplane surface. This work aims to describe in detail the results that can be achieved by using the proposed LMS with window learning algorithm in information systems that employ the methodology of neural network for the purposes of classification.
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Cui, Xiangchen. "Mean-Square Error Bounds and Perfect Sampling for Conditional Coding." DigitalCommons@USU, 2000. https://digitalcommons.usu.edu/etd/7107.

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In this dissertation, new theoretical results are obtained for bounding convergence and mean-square error in conditional coding. Further new statistical methods for the practical application of conditional coding are developed. Criteria for the uniform convergence are first examined. Conditional coding Markov chains are aperiodic, π-irreducible, and Harris recurrent. By applying the general theories of uniform ergodicity of Markov chains on genera l state space, one can conclude that conditional coding Markov cha ins are uniformly ergodic and further, theoretical convergence rates based on Doeblin's condition can be found. Conditional coding Markov chains can be also viewed as having finite state space. This allows use of techniques to get bounds on the second largest eigenvalue which lead to bounds on convergence rate and the mean-square error of sample averages. The results are applied in two examples showing that these bounds are useful in practice. Next some algorithms for perfect sampling in conditional coding are studied. An application of exact sampling to the independence sampler is shown to be equivalent to standard rejection sampling. In case of single-site updating, traditional perfect sampling is not directly applicable when the state space has large cardinality and is not stochastically ordered, so a new procedure is developed that gives perfect samples at a predetermined confidence interval. In last chapter procedures and possibilities of applying conditional coding to mixture models are explored. Conditional coding can be used for analysis of a finite mixture model. This methodology is general and easy to use.
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Fodor, Balázs [Verfasser]. "Contributions to Statistical Modeling for Minimum Mean Square Error Estimation in Speech Enhancement / Balázs Fodor." Aachen : Shaker, 2015. http://d-nb.info/1070151815/34.

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Xing, Chengwen, and 邢成文. "Linear minimum mean-square-error transceiver design for amplify-and-forward multiple antenna relaying systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B44769738.

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Nicolson, Aaron M. "Deep Learning for Minimum Mean-Square Error and Missing Data Approaches to Robust Speech Processing." Thesis, Griffith University, 2020. http://hdl.handle.net/10072/399974.

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Speech corrupted by background noise (or noisy speech) can cause misinterpretation and fatigue during phone and conference calls, and for hearing aid users. Noisy speech can also severely impact the performance of speech processing systems such as automatic speech recognition (ASR), automatic speaker verification (ASV), and automatic speaker identification (ASI) systems. Currently, deep learning approaches are employed in an end-to-end fashion to improve robustness. The target speech (or clean speech) is used as the training target or large noisy speech datasets are used to facilitate multi-condition training. In this dissertation, we propose competitive alternatives to the preceding approaches by updating two classic robust speech processing techniques using deep learning. The two techniques include minimum mean-square error (MMSE) and missing data approaches. An MMSE estimator aims to improve the perceived quality and intelligibility of noisy speech. This is accomplished by suppressing any background noise without distorting the speech. Prior to the introduction of deep learning, MMSE estimators were the standard speech enhancement approach. MMSE estimators require the accurate estimation of the a priori signal-to-noise ratio (SNR) to attain a high level of speech enhancement performance. However, current methods produce a priori SNR estimates with a large tracking delay and a considerable amount of bias. Hence, we propose a deep learning approach to a priori SNR estimation that is significantly more accurate than previous estimators, called Deep Xi. Through objective and subjective testing across multiple conditions, such as real-world non-stationary and coloured noise sources at multiple SNR levels, we show that Deep Xi allows MMSE estimators to produce the highest quality enhanced speech amongst all clean speech magnitude spectrum estimators. Missing data approaches improve robustness by performing inference only on noisy speech features that reliably represent clean speech. In particular, the marginalisation method was able to significantly increase the robustness of Gaussian mixture model (GMM)-based speech classification systems (e.g. GMM-based ASR, ASV, or ASI systems) in the early 2000s. However, deep neural networks (DNNs) used in current speech classification systems are non-probabilistic, a requirement for marginalisation. Hence, multi-condition training or noisy speech pre-processing is used to increase the robustness of DNN-based speech classification systems. Recently, sum-product networks (SPNs) were proposed, which are deep probabilistic graphical models that can perform the probabilistic queries required for missing data approaches. While available toolkits for SPNs are in their infancy, we show through an ASI task that SPNs using missing data approaches could be a strong alternative for robust speech processing in the future. This dissertation demonstrates that MMSE estimators and missing data approaches are still relevant approaches to robust speech processing when assisted by deep learning.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Eng & Built Env
Science, Environment, Engineering and Technology
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Septarina, Septarina. "Micro-Simulation of the Roundabout at Idrottsparken Using Aimsun : A Case Study of Idrottsparken Roundabout in Norrköping, Sweden." Thesis, Linköpings universitet, Kommunikations- och transportsystem, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-79964.

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Microscopic traffic simulation is useful tool in analysing traffic and estimating the capacity and level of service of road networks. In this thesis, the four legged Idrottsparken roundabout in the city of Norrkoping in Sweden is analysed by using the microscopic traffic simulation package AIMSUN. For this purpose, data regarding traffic flow counts, travel times and queue lengths were collected for three consecutive weekdays during both the morning and afternoon peak periods. The data were then used in model building for simulation of traffic of the roundabout. The Root Mean Square Error (RMSE) method is used to get the optimal parameter value between queue length and travel time data and validation of travel time data are carried out to obtain the basic model which represents the existing condition of the system. Afterward, the results of the new models were evaluated and compared to the results of a SUMO model for the same scenario model. Based on calibrated and validated model, three alternative scenarios were simulated and analysed to improve efficiency of traffic network in the roundabout. The three scenarios includes: (1) add one free right turn in the north and east sections; (2) add one free right turn in the east and south sections; and (3) addition of one lane in roundabout. The analysis of these scenarios shows that the first and second scenario are only able to reduce the queue length and travel time in two or three legs, while the third scenario is not able to improve the performance of the roundabout. In this research, it can be concluded that the first scenario is considered as the best scenario compared to the second scenario and the third scenario. The comparison between AIMSUN and SUMO for the same scenario shows that the results have no significance differences. In calibration process, to get the optimal parameter values between the model measurements and the field measurements, both of AIMSUN and SUMO uses two significantly influencing parametersfor queue and travel time. AIMSUN package uses parameter of driver reaction time and the maximum acceleration, while SUMO package uses parameter of driver imperfection and also the driver rection time.
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Nassr, Husam, and Kurt Kosbar. "PERFORMANCE EVALUATION FOR DECISION-FEEDBACK EQUALIZER WITH PARAMETER SELECTION ON UNDERWATER ACOUSTIC COMMUNICATION." International Foundation for Telemetering, 2017. http://hdl.handle.net/10150/626999.

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This paper investigates the effect of parameter selection for the decision feedback equalization (DFE) on communication performance through a dispersive underwater acoustic wireless channel (UAWC). A DFE based on minimum mean-square error (MMSE-DFE) criterion has been employed in the implementation for evaluation purposes. The output from the MMSE-DFE is input to the decoder to estimate the transmitted bit sequence. The main goal of this experimental simulation is to determine the best selection, such that the reduction in the computational overload is achieved without altering the performance of the system, where the computational complexity can be reduced by selecting an equalizer with a proper length. The system performance is tested for BPSK, QPSK, 8PSK and 16QAM modulation and a simulation for the system is carried out for Proakis channel A and real underwater wireless acoustic channel estimated during SPACE08 measurements to verify the selection.
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Ding, Minhua. "Multiple-input multiple-output wireless system designs with imperfect channel knowledge." Thesis, Kingston, Ont. : [s.n.], 2008. http://hdl.handle.net/1974/1335.

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Thompson, Grant. "Effects of DEM resolution on GIS-based solar radiation model output: A comparison with the National Solar Radiation Database." University of Cincinnati / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1258663688.

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Kulkarni, Aditya. "Performance Analysis of Zero Forcing and Minimum Mean Square Error Equalizers on Multiple Input Multiple Output System on a Spinning Vehicle." International Foundation for Telemetering, 2014. http://hdl.handle.net/10150/577482.

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ITC/USA 2014 Conference Proceedings / The Fiftieth Annual International Telemetering Conference and Technical Exhibition / October 20-23, 2014 / Town and Country Resort & Convention Center, San Diego, CA
Channel equalizers based on minimum mean square error (MMSE) and zero forcing (ZF) criteria have been formulated for a general scalable multiple input multiple output (MIMO) system and implemented for a 2x2 MIMO system with spatial multiplexing (SM) for Rayleigh channel associated with additive white Gaussian noise. A model to emulate transmitters and receivers on a spinning vehicle has been developed. A transceiver based on the BLAST architecture is developed in this work. A mathematical framework to explain the behavior of the ZF and MMSE equalizers is formulated. The performance of the equalizers has been validated for a case with one of the communication entities being a spinning aero vehicle. Performance analysis with respect to variation of angular separation between the antennas and relative antenna gain for each case is presented. Based on the simulation results a setup with optimal design parameters for placement of antennas, choice of the equalizers and transmit power is proposed.
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Books on the topic "Mean square Canny error"

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Clements, Michael P. On the limitations of comparing mean square forecast error. Oxford: Oxford University, Institute of Economics and Statistics, 1992.

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G, Kalit, and Ames Research Center, eds. Mean-square error bounds for reduced-order linear state estimators. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1987.

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Baram, Yoram. Mean-square error bounds for reduced-order linear state estimators. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1987.

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G, Kalit, and Ames Research Center, eds. Mean-square error bounds for reduced-order linear state estimators. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1987.

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Hoque, Asraul. The exact multiperiod mean-square forecast error for the first-order autoregressive model. London: London School of Economics, 1986.

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Magnus, Jan R. The exact multiperiod mean-square forecast error for the first-order autoregressive modelwith an intercept. London: National Institute of Economic and Social Research, 1988.

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Magnus, Jan R. The exact multiperiod mean-square forecast error for the first-order autoregressive model with an intercept. London: International Centre for Economics and Related Disciplines, 1988.

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Cardot, Hervé, and Pascal Sarda. Functional Linear Regression. Edited by Frédéric Ferraty and Yves Romain. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.013.2.

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This article presents a selected bibliography on functional linear regression (FLR) and highlights the key contributions from both applied and theoretical points of view. It first defines FLR in the case of a scalar response and shows how its modelization can also be extended to the case of a functional response. It then considers two kinds of estimation procedures for this slope parameter: projection-based estimators in which regularization is performed through dimension reduction, such as functional principal component regression, and penalized least squares estimators that take into account a penalized least squares minimization problem. The article proceeds by discussing the main asymptotic properties separating results on mean square prediction error and results on L2 estimation error. It also describes some related models, including generalized functional linear models and FLR on quantiles, and concludes with a complementary bibliography and some open problems.
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Book chapters on the topic "Mean square Canny error"

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Shekhar, Shashi, and Hui Xiong. "Root-Mean-Square Error." In Encyclopedia of GIS, 979. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_1142.

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Weik, Martin H. "minimum mean-square error filtering." In Computer Science and Communications Dictionary, 1022. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_11569.

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Weik, Martin H. "minimum mean-square error restoration." In Computer Science and Communications Dictionary, 1022. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_11570.

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Liu, Yan. "Mean Square Error of Survey Estimates." In Encyclopedia of Quality of Life and Well-Being Research, 3892–93. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_1754.

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Liu, Yan. "Mean Square Error of Survey Estimates." In Encyclopedia of Quality of Life and Well-Being Research, 1–3. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-319-69909-7_1754-2.

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Principe, Jose C., Yadunandana N. Rao, and Deniz Erdogmus. "Error Whitening Wiener Filters: Theory and Algorithms." In Least-Mean-Square Adaptive Filters, 445–89. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471461288.ch10.

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Alexander, S. Thomas. "The Mean Square Error (MSE) Performance Criteria." In Adaptive Signal Processing, 8–33. New York, NY: Springer New York, 1986. http://dx.doi.org/10.1007/978-1-4612-4978-8_2.

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Gründinger, Andreas. "Mean Square Error Transceiver Design for Additive Fading." In Statistical Robust Beamforming for Broadcast Channels and Applications in Satellite Communication, 77–125. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29578-3_4.

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Deng, Chengzhi. "Minimum Mean Square Error Estimator for Shearlet Coefficients Reconstruction." In Lecture Notes in Electrical Engineering, 737–44. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-2169-2_88.

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Qiang, Luya, Hao Shi, Meng Ge, Haoran Yin, Nan Li, Longbiao Wang, Sheng Li, and Jianwu Dang. "Speech Dereverberation Based on Scale-Aware Mean Square Error Loss." In Communications in Computer and Information Science, 55–63. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-92307-5_7.

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Conference papers on the topic "Mean square Canny error"

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Varma, D. R. Deekshitha, and R. Priyanka. "Performance Monitoring of Novel Iris Detection System using Sobel Algorithm in Comparison with Canny Algorithm by Minimizing the Mean Square Error." In 2022 3rd International Conference on Intelligent Engineering and Management (ICIEM). IEEE, 2022. http://dx.doi.org/10.1109/iciem54221.2022.9853127.

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Mangileva, Daria, Alexander Kursanov, Alena Tsvetkova, Olesya Bernikova, Alexey Ovechkin, Maria Grubbe, Jan Azarov, and Leonid Katsnelson. "Preprocessing Images Algorithm without Gaussian Shaped Particles for PIV Analysis and Imaging Vortices on the Epicardial Surface." In 31th International Conference on Computer Graphics and Vision. Keldysh Institute of Applied Mathematics, 2021. http://dx.doi.org/10.20948/graphicon-2021-3027-519-528.

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e intense movement of the heart and the presence of blood on surface, the application of the necessary small markers is rather difficult, and the use of luminous chemicals would harm physiological functioning. Moreover, these videos contain motion artifacts that complicate further analysis with Particle Image Velocimetry. In this paper, an image preprocessing algorithm was proposed. It is based on approximate tracking individual fragments using the Mean Squared Error for the matrix. The result is binary images where small points are built instead of each fragment. In this study, the proposed algorithm showed better results in comparison with the most suitable filtering methods for specific frames, namely, the Sobel filter and the Canny edge detector. This can be partially explained by the higher density of vector fields due to the absence of unreliable vectors. Thus, the proposed method, unlike others, allows to get vector fields with visible vortex-like mechanical movements.
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Kolmer, Haden P., Clark M. Cunningham, and Mohammed F. Al-Dushaishi. "ROP Optimization of Lateral Wells in SW Oklahoma: Artificial Neural Network Approach." In ASME 2022 Onshore Petroleum Technology Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/optc2022-91464.

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Abstract Rate of Penetration (ROP) optimization has played a key role in the economic return and value of both onshore and offshore wells by decreasing drilling time thereby increasing the net present value (NPV) of the localized field. In this study, an Artificial Neural Network (ANN) model is developed to accurately model the ROP of a well in SW Oklahoma to optimize the drilling process. A parametric study was conducted to showcase the effect of operational parameters on the ROP-ANN model and to minimize error and increase accuracy. The number of neurons and hidden layers within the model are optimized based on the lowest Mean Square Error (MSE) and highest R2. A comparative study was comprised of one well in Southern Oklahoma targeting the Caney Shale. The well is about 10,000″ vertical with a 2-mile lateral with a maximum inclination of 78° and Dogleg Severity (DLS) of 12°/100ft. UCS was incorporated into the model to geomechanically differentiate between shale, sandstone, and limestone. The input drilling data is weighed against ROP showcasing the impact of each parameter on ROP. From this and further proven in the results, RPM, WOB, and UCS greatly effect ROP per foot based on the sensitivity analysis but steadily decline as the critical value is achieved. The major advantage of this study is developing an accurate ANN model for onshore North American shale plays in understanding the lithological impact of UCS and high lateral deviation on ROP which can be used in pre-planning to optimize the drilling processes.
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Ephraim, Y. "On minimum mean square error speech enhancement." In [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing. IEEE, 1991. http://dx.doi.org/10.1109/icassp.1991.150509.

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Gusi-Amigo, Adria, Pau Ciosas, and Luc Vandendorpe. "Mean square error performance of sample mean and sample median estimators." In 2016 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2016. http://dx.doi.org/10.1109/ssp.2016.7551739.

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Hua Peng and Naofal Al-Dhahir. "Sparse minimum mean square error(MMSE) blind beamformer." In 2015 IEEE International Wireless Symposium (IWS). IEEE, 2015. http://dx.doi.org/10.1109/ieee-iws.2015.7164517.

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Tsai, Fu Y., and Huei Peng. "Minimum mean square error linear predictor with rounding." In Visual Communications and Image Processing '95, edited by Lance T. Wu. SPIE, 1995. http://dx.doi.org/10.1117/12.206750.

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Bhatnagar, Raj K., and Robert L. Williams. "Templates with lower mean square error for ATR." In AeroSense '97, edited by Edmund G. Zelnio. SPIE, 1997. http://dx.doi.org/10.1117/12.281565.

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William, Peter E., and Michael W. Hoffman. "Error Entropy and Mean Square Error Minimization for Lossless Image Compression." In 2006 International Conference on Image Processing. IEEE, 2006. http://dx.doi.org/10.1109/icip.2006.312813.

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Jia, G. Q., Y. Pan, J. J. Du, and X. H. Ji. "Symbol detection aided minimum mean square error interference alignment." In 2018 IEEE MTT-S International Wireless Symposium (IWS). IEEE, 2018. http://dx.doi.org/10.1109/ieee-iws.2018.8400860.

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Reports on the topic "Mean square Canny error"

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Sun, Winston Y. Linear adaptive noise-reduction filters for tomographic imaging: Optimizing for minimum mean square error. Office of Scientific and Technical Information (OSTI), April 1993. http://dx.doi.org/10.2172/10148667.

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Bruder, Brittany L., Katherine L. Brodie, Tyler J. Hesser, Nicholas J. Spore, Matthew W. Farthing, and Alexander D. Renaud. guiBath y : A Graphical User Interface to Estimate Nearshore Bathymetry from Hovering Unmanned Aerial System Imagery. Engineer Research and Development Center (U.S.), February 2021. http://dx.doi.org/10.21079/11681/39700.

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This US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, technical report details guiBathy, a graphical user interface to estimate nearshore bathymetry from imagery collected via a hovering Unmanned Aerial System (UAS). guiBathy provides an end-to-end solution for non-subject-matter-experts to utilize commercia-off-the-shelf UAS to collect quantitative imagery of the nearshore by packaging robust photogrammetric and signal-processing algorithms into an easy-to-use software interface. This report begins by providing brief background on coastal imaging and the photogrammetry and bathymetric inversion algorithms guiBathy utilizes, as well as UAS data collection requirements. The report then describes guiBathy software specifications, features, and workflow. Example guiBathy applications conclude the report with UAS bathymetry measurements taken during the 2020 Atlantic Hurricane Season, which compare favorably (root mean square error = 0.44 to 0.72 m; bias = -0.35 to -0.11 m) with in situ survey measurements. guiBathy is a standalone executable software for Windows 10 platforms and will be freely available at www.github.com/erdc.
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Pradhan, Nawa Raj. Estimating growing-season root zone soil moisture from vegetation index-based evapotranspiration fraction and soil properties in the Northwest Mountain region, USA. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/42128.

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A soil moisture retrieval method is proposed, in the absence of ground-based auxiliary measurements, by deriving the soil moisture content relationship from the satellite vegetation index-based evapotranspiration fraction and soil moisture physical properties of a soil type. A temperature–vegetation dryness index threshold value is also proposed to identify water bodies and underlying saturated areas. Verification of the retrieved growing season soil moisture was performed by comparative analysis of soil moisture obtained by observed conventional in situ point measurements at the 239-km2 Reynolds Creek Experimental Watershed, Idaho, USA (2006–2009), and at the US Climate Reference Network (USCRN) soil moisture measurement sites in Sundance, Wyoming (2012–2015), and Lewistown, Montana (2014–2015). The proposed method best represented the effective root zone soil moisture condition, at a depth between 50 and 100 cm, with an overall average R2 value of 0.72 and average root mean square error (RMSE) of 0.042.
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Al-Qadi, Imad, Qingqing Cao, Lama Abufares, Siqi Wang, Uthman Mohamed Ali, and Greg Renshaw. Moisture Content and In-place Density of Cold-Recycling Treatments. Illinois Center for Transportation, May 2022. http://dx.doi.org/10.36501/0197-9191/22-007.

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Cold-recycling treatments are gaining popularity in the United States because of their economic and environmental benefits. Curing is the most critical phase for these treatments. Curing is the process where emulsion breaks and water evaporates, leaving residual binder in the treated material. In this process, the cold-recycled mix gains strength. Sufficient strength is required before opening the cold-treated layer to traffic or placing an overlay. Otherwise, premature failure, related to insufficient strength and trapped moisture, would be expected. However, some challenges arise from the lack of relevant information and specifications to monitor treatment curing. This report presents the outcomes of a research project funded by the Illinois Department for Transportation to investigate the feasibility of using the nondestructive ground-penetrating radar (GPR) for density and moisture content estimation of cold-recycled treatments. Monitoring moisture content is an indicator of curing level; treated layers must meet a threshold of maximum allowable moisture content (2% in Illinois) to be considered sufficiently cured. The methodology followed in this report included GPR numerical simulations and GPR indoor and field tests for data sources. The data were used to correlate moisture content to dielectric properties calculated from GPR measurements. Two models were developed for moisture content estimation: the first is based on numerical simulations and the second is based on electromagnetic mixing theory and called the Al-Qadi-Cao-Abufares (ACA) model. The simulation model had an average error of 0.33% for moisture prediction for five different field projects. The ACA model had an average error of 2% for density prediction and an average root-mean-square error of less than 0.5% for moisture content prediction for both indoor and field tests. The ACA model is presented as part of a developed user-friendly tool that could be used in the future to continuously monitor curing of cold-recycled treatments.
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Brodie, Katherine, Brittany Bruder, Richard Slocum, and Nicholas Spore. Simultaneous mapping of coastal topography and bathymetry from a lightweight multicamera UAS. Engineer Research and Development Center (U.S.), August 2021. http://dx.doi.org/10.21079/11681/41440.

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A low-cost multicamera Unmanned Aircraft System (UAS) is used to simultaneously estimate open-coast topography and bathymetry from a single longitudinal coastal flight. The UAS combines nadir and oblique imagery to create a wide field of view (FOV), which enables collection of mobile, long dwell timeseries of the littoral zone suitable for structure-from motion (SfM), and wave speed inversion algorithms. Resultant digital surface models (DSMs) compare well with terrestrial topographic lidar and bathymetric survey data at Duck, NC, USA, with root-mean-square error (RMSE)/bias of 0.26/–0.05 and 0.34/–0.05 m, respectively. Bathymetric data from another flight at Virginia Beach, VA, USA, demonstrates successful comparison (RMSE/bias of 0.17/0.06 m) in a secondary environment. UAS-derived engineering data products, total volume profiles and shoreline position, were congruent with those calculated from traditional topo-bathymetric surveys at Duck. Capturing both topography and bathymetry within a single flight, the presented multicamera system is more efficient than data acquisition with a single camera UAS; this advantage grows for longer stretches of coastline (10 km). Efficiency increases further with an on-board Global Navigation Satellite System–Inertial Navigation System (GNSS-INS) to eliminate ground control point (GCP) placement. The Appendix reprocesses the Virginia Beach flight with the GNSS–INS input and no GCPs.
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Collins, Clarence O., and Tyler J. Hesser. altWIZ : A System for Satellite Radar Altimeter Evaluation of Modeled Wave Heights. Engineer Research and Development Center (U.S.), February 2021. http://dx.doi.org/10.21079/11681/39699.

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This Coastal and Hydraulics Engineering Technical Note (CHETN) describes the design and implementation of a wave model evaluation system, altWIZ, which uses wave height observations from operational satellite radar altimeters. The altWIZ system utilizes two recently released altimeter databases: Ribal and Young (2019) and European Space Agency Sea State Climate Change Initiative v.1.1 level 2 (Dodet et al. 2020). The system facilitates model evaluation against 1 Hz1 altimeter data or a product created by averaging altimeter data in space and time around model grid points. The system allows, for the first time, quantitative analysis of spatial model errors within the U.S. Army Corps of Engineers (USACE) Wave Information Study (WIS) 30+ year hindcast for coastal United States. The system is demonstrated on the WIS 2017 Atlantic hindcast, using a 1/2° basin scale grid and a 1/4° regional grid of the East Coast. Consistent spatial patterns of increased bias and root-mean-square-error are exposed. Seasonal strengthening and weakening of these spatial patterns are found, related to the seasonal variation of wave energy. Some model errors correspond to areas known for high currents, and thus wave-current interaction. In conjunction with the model comparison, additional functions for pairing altimeter measurements with buoy data and storm tracks have been built. Appendices give information on the code access (Appendix I), organization and files (Appendix II), example usage (Appendix III), and demonstrating options (Appendix IV).
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