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Novel Convolution Kernels for Computer Vision and Shape Analysis based on Electromagnetism [article]

Dominique Beaini, Sofiane Achiche, Yann-Seing Law-Kam Cio, Maxime Raison
2018 arXiv   pre-print
The objective of this paper is to present a novel convolution kernels, based on principles of electromagnetic potentials and fields, for a general use in computer vision and to demonstrate its usage for  ...  Therefore, this paper focuses on the development of the electromagnetic kernels and on their application on images for shape and stroke analysis.  ...  Acknowledgment We would like to thank NSERC, through the discovery grant program, and FRQNT/INTER for their financial support as well as MEDITIS (Biomedical technologies training program) through NSERC  ... 
arXiv:1806.07996v1 fatcat:tgmo3yeu5va2nlmxsbizszztsi

Vision-Based Fall Detection Using Dense Block With Multi-Channel Convolutional Fusion Strategy

Xi Cai, Xinyue Liu, Mingyue An, Guang Han
2021 IEEE Access  
Different from most traditional vision-based methods relying on hand-crafted features, fall detection methods based on deep learning technology can automatically mine features to detect fall events due  ...  To solve the abovementioned problem, we propose a fall detection method based on dense block with a multi-channel convolutional fusion (MCCF) strategy.  ...  PROPOSED METHOD In this work, a novel method based on MCCF-DenseBlock is proposed for fall detection.  ... 
doi:10.1109/access.2021.3054469 fatcat:wizqwlkbjvdvtaknpuuqyy36fa

Front Matter: Volume 10696

Jianhong Zhou, Petia Radeva, Dmitry Nikolaev, Antanas Verikas
2018 Tenth International Conference on Machine Vision (ICMV 2017)  
The papers in this volume were part of the technical conference cited on the cover and title page. Papers were selected and subject to review by the editors and conference program committee.  ...  .  The last two digits indicate publication order within the volume using a Base 36 numbering system employing both numerals and letters. These two-number sets start with 00, 01, 02, 03,  ...  0N Graphic matching based on shape contexts and reweighted random walks [10696-59] 10696 0O A comparative analysis of image features between weave embroidered Thangka and piles embroidered Thangka  ... 
doi:10.1117/12.2319685 dblp:conf/icmv/X17 fatcat:jb7w6d2ewbe57gaqkvxcumxpum

Front Matter: Volume 10033

2016 Eighth International Conference on Digital Image Processing (ICDIP 2016)  
.  The last two digits indicate publication order within the volume using a Base 36 numbering system employing both numerals and letters. These two-number sets start with 00, 01, 02, 03, 04,  ...  Publication of record for individual papers is online in the SPIE Digital Library. Paper Numbering: Proceedings of SPIE follow an e-First publication model.  ...  ] SESSION 17 COMPUTER VISION AND VISUALIZATION 10033 5M Generating dynamic street view images [10033-3] 10033 5N A real time vision system for traffic surveillance at intersections [10033-160]  ... 
doi:10.1117/12.2257252 fatcat:v2ipfp2mp5gedjypzpecahpo7e

Deep Convolution Neural Network for Big Data Medical Image Classification

Rehan Ashraf, Muhammad Asif Habib, Muhammad Akram, Muhammad Ahsan Latif, Muhammad Sheraz Arshad Malik, Muhammad Awais, Saadat Hanif Dar, Toqeer Mahmood, Muhammad Yasir, Zahoor Abbas
2020 IEEE Access  
Due to recent developments in imaging technology, classifying medical images in an automatic way is an open research problem for researchers of computer vision.  ...  Deep learning is one of the most unexpected machine learning techniques which is being used in many applications like image classification, image analysis, clinical archives and object recognition.  ...  We have proposed a novel deep convolution network-based approach that is assist of doctors and physicians in making reasonable decisions.  ... 
doi:10.1109/access.2020.2998808 fatcat:e3fo3fh3encujji643ikghklyy

Bibliography [chapter]

Scott Krig
2014 Computer Vision Metrics  
Vedaldi, A., and S. Soatto. "Quick Shift and Kernel Methods for Mode Seeking." European Conference on Computer Vision, 2008. 268. Vincent, L., and P. Soille.  ...  International Journal on Computer Vision (2013). 225. Fowers, Spencer G., D. J. Lee, Dan Ventura, and Doran K. Wilde. "A Novel, Efficient, Tree-Based Descriptor and Matching Algorithm (BASIS)."  ... 
doi:10.1007/978-1-4302-5930-5_13 fatcat:bnsbslueindjrdsxjvt5ulcozq

Vision-based Fall Detection with Multi-task Hourglass Convolutional Auto-encoder

Xi Cai, Suyuan Li, Xinyue Liu, Guang Han
2020 IEEE Access  
Different from most conventional vision-based fall detection methods typically relying on hand-crafted features, fall detection methods based on deep learning techniques can automatically learn features  ...  To solve the above problem, we propose a vision-based fall detection method using multi-task hourglass convolutional auto-encoder (HCAE).  ...  PROPOSED METHOD In this work, a novel method based on the HCAE with HRUs and a multi-task mechanism is proposed for fall detection.  ... 
doi:10.1109/access.2020.2978249 fatcat:hhtygpuusvaadlrjzxrjz6jt5u

A Robust SVM Color-Based Food Segmentation Algorithm for the Production Process of a Traditional Carasau Bread

Katiuscia Mannaro, Matteo Baire, Alessandro Fanti, Matteo Bruno Lodi, Luca Didaci, Alessandro Fedeli, Luisanna Cocco, Andrea Randazzo, Giuseppe Mazzarella, Giorgio Fumera
2022 IEEE Access  
We implemented an image acquisition system and created an efficient machine learning algorithm, based on support vector machines, for the segmentation and estimation of image measurements for Carasau bread  ...  The study focuses on one of the most critical activities for obtaining an efficient degree of automation: the estimation of the size and shape of the bread sheets during the production phase, to study  ...  S.N.C for participating in this study and for the information they freely provided.(Matteo Baire and Katiuscia Mannaro contributed equally to this work.)  ... 
doi:10.1109/access.2022.3147206 fatcat:pitz2vqp6rcfvjhoxuf256cpra

Computing the Spatial Probability of Inclusion inside Partial Contours for Computer Vision Applications [article]

Dominique Beaini, Sofiane Achiche, Fabrice Nonez, Maxime Raison
2019 arXiv   pre-print
In Computer Vision, edge detection is one of the favored approaches for feature and object detection in images since it provides information about their objects boundaries.  ...  To answer this objective, we developed a new approach that uses electromagnetic convolutions and repulsion optimization to compute the required probabilities.  ...  Acknowledgment We would like to thank NSERC, through the discovery grant program RGPIN-2014-06289, and FRQNT/INTER for their financial support as well as MEDITIS (Biomedical technologies training program  ... 
arXiv:1806.01339v2 fatcat:56si5gxy4ne6bo7pbpdrmpvowi

Attendee List

2020 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)  
Sørensen 41 Design and test an intelligent irrigation system for small surfaces Romania Mircea Nitulescu 42 Vision-Based Drowsiness Detection System Using Convolutional Neural Networks Turkey  ...  14 IoT Novel ACO-OFDM System Based on Fast Walsh Hadamard Transform Turkey Busra Avcı Design and Implementation of a Novel Power Conditioner for Linear Induction Launchers Turkey Abdulkadir Balikci 422  ... 
doi:10.1109/icecce49384.2020.9179198 fatcat:ryry4suqzrfh3ch2v3veh4z6ei

Deep learning and machine vision for food processing: A survey

Lili Zhu, Petros Spachos, Erica Pensini, Konstantinos N. Plataniotis
2021 Current Research in Food Science  
In this paper, we provide an overview on the traditional machine learning and deep learning methods, as well as the machine vision techniques that can be applied to the field of food processing.  ...  Nowadays, the development of machine vision can greatly assist researchers and industries in improving the efficiency of food processing.  ...  convolution kernel W.  ... 
doi:10.1016/j.crfs.2021.03.009 pmid:33937871 pmcid:PMC8079277 fatcat:cqzvzbwwjrdulnve6shf7o2agu

Physics-Informed Deep Neural Networks for Transient Electromagnetic Analysis

Oameed Noakoasteen, Shu Wang, Zhen Peng, Christos Christodoulou
2020 IEEE Open Journal of Antennas and Propagation  
INDEX TERMS Computer vision, electromagnetics, finite difference methods, machine learning, recurrent neural networks, unsupervised learning.  ...  In this paper, we propose a deep neural network based model to predict the time evolution of field values in transient electrodynamics.  ...  ACKNOWLEDGMENT The authors would like to thank the University of New Mexico Center for Advanced Research Computing, supported in part by the National Science Foundation, for providing the high-performance  ... 
doi:10.1109/ojap.2020.3013830 fatcat:civbopkuyjaptogk6ddil2fs2m

Automatic Defect Identification Method for Magnetic Particle Inspection of Bearing Rings Based on Visual Characteristics and High-Level Features

Yun Yang, Yao Yang, Long Li, Cuili Chen, Zhou Min
2022 Applied Sciences  
Due to the complexity of bearing ring surfaces in inspection, automatic detection for bearing rings based on image processing is difficult to apply.  ...  Therefore, we proposed a bearing ring defect identification method based on visual characteristics and high-level features.  ...  (a) Original image; (b) The method based on shape features and SVM; (c) The method based on Hu moment invariant feature and BP; (d) The method based on SIFT features and SVM; (e) Our method.  ... 
doi:10.3390/app12031293 fatcat:7psw2yjfkbh4bca2sa7w2fdo54

Automated Grapevine Cultivar Identification via Leaf Imaging and Deep Convolutional Neural Networks: A Proof-of-Concept Study Employing Primary Iranian Varieties

Amin Nasiri, Amin Taheri-Garavand, Dimitrios Fanourakis, Yu-Dong Zhang, Nikolaos Nikoloudakis
2021 Plants  
For on-time evaluations, molecular genetics have been successfully performed, though in many instances, they are limited by the lack of referable data or the cost element.  ...  This paper presents a convolutional neural network (CNN) framework for automatic identification of grapevine cultivar by using leaf images in the visible spectrum (400–700 nm).  ...  We thank the laboratory staff for their contributions, continued diligence, and dedication to their craft. Conflicts of Interest: No potential conflict of interest was reported by the authors.  ... 
doi:10.3390/plants10081628 pmid:34451673 pmcid:PMC8399703 fatcat:lp6ehzd5unaofcbs7u77edjpgi

2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57

2019 IEEE Transactions on Geoscience and Remote Sensing  
., and Drake, V.A., Insect Biological Parameter Estimation Based on the Invariant Target Parameters of the Scattering Matrix; TGRS Aug. 2019 6212-6225 Hu, C., see Zhang, M., TGRS Sept. 2019 6666-6674  ...  and Hanssen, R.F., Incorporating Temporary Coherent Li, X., Yeo, T.S., Yang, Y., Chi, C., Zuo, F., Hu, X., and Pi, Y., Refo-cusing and Zoom-In Polar Format Algorithm for Curvilinear Spotlight SAR Imaging  ...  ., +, TGRS June 2019 4121-4145 Computer graphics A Novel Octree-Based 3-D Fully Convolutional Neural Network for Point Cloud Classification in Road Environment.  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4
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