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arXiv 2021年

作者： Shehata, Mohamed Abou-Kreisha, Mohamed Taha Elnashar, Hany Systems & Computers Engineering Department Faculty of Engineering Al-Azhar University Egypt Mathematical & Computer Science Department Faculty of Science Al-Azhar University Egypt Project Development Unite Faculty of Computers and Artificial Intelligent Beni-Suef University

Automated Vehicle License Plate (VLP) detection and recognition have ended up being a significant research issue as of late. VLP localization and recognition are some of the most essential techniques for managing traffic using digital techniques. In this paper, four smart systems are developed to recognize Egyptian vehicles' license plates. Two systems are based on character recognition, which are (System1: Characters Recognition with Classical Machine Learning) and (System2: Characters Recognition with Deep Machine Learning). The other two systems are based on the whole plate recognition which are (System3: Whole License Plate Recognition with Classical Machine Learning) and (System4: Whole License Plate Recognition with Deep Machine Learning). We use object detection algorithms, and machine learning based object recognition algorithms. The performance of the developed systems has been tested on real images, and the experimental results demonstrate that the best detection accuracy rate for VLP is provided by using the deep learning method. Where the VLP detection accuracy rate is better than the classical system by 32%. However, the best detection accuracy rate for Vehicle License Plate Arabic Character (VLPAC) is provided by using the classical method. Where VLPAC detection accuracy rate is better than the deep learning-based system by 6%. Also, the results show that deep learning is better than the classical technique used in VLP recognition processes. Where the recognition accuracy rate is better than the classical system by 8%. Finally, the paper output recommends a robust VLP recognition system based on both statistical and deep machine learning. © 2021, CC BY.

关键词： Deep learning

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Symposia lectures

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Journal of Biosciences 1999年第1期24卷 5-31页

作者： F. Parak A. Ostermann G. U. Nienhaus Nobuo Niimura William A. Eaton Stephen J. Hagen Eric R. Henry James Hofrichter Gouri Jas Lisa Lapidus Victor Muñoz Chih-chen Wang Abani Bhuyan Javant Udgaonkar Heinz Rüterians Derek N. Woolfson M. D. Finucane J. H. Lees M. J. Pandya G. Spooner M. Tuna Wilma K. Olson K. V. R. Chary E. Westhof I. G. Wool C. C. Correll V. I. Ivanov S. A. Bondarenko E. M. Zdobnov A. D. Beniaminov E. E. Minyat N. B. Ulyanov Dale B. Wigley Nobuo Shimamoto Takashi Kinebuchi Hiroyuki Kabata Osamu Kurosawa Masao Washizu Barbara Baird David Holowka H. Belrhali P. Nollert A. Royant J. P. Rosenbusch E. M. Landau E. Pebav-Peyroula Anil K. Lala Patrick R. D’Silva Daniela Pietrobon Paolo Pinton Paulo Magalhaes Anna Chiesa Marisa Brini Tullio Pozzan Rosario Rizzuto M. Montai Shu-Rong Wang José L. Carrascosa B. Bhattacharyya Ian A. Wilson Dinakar M. Salunke Kurt Drickamer Anne Imberty A. Surolia Louise N. Johnson Michal Neeman S. M. Prince K. McLuskey R. J. Cogdell K. McAuley N. W. Isaacs G. Venturoli F. Drepper J. C. Williams J. P. Allen X. Lin P. Mathis R. van Grondelle Wolfgang Junge T. Tsukihara K. Shinzawa-Itoh R. Nakashima E. Yamashita M. J. Fei N. Inoue T. Tomizaki C. Peters Libeu S. Yoshikawa Patrick Chaussepied Keiichi Namba Marie-France Carlier Fariza Ressacl Valerie Laurent Thomas Loisel Coumaran Egile Philippe Sansonetti Dominique Pantaloni Manju Bansal E. W. Knapp M. G. Ullmann A. Amadei B. L. de Groot M. A. Ceruso M. Paci H. J. C. Berendsen A. Di Nola V. Di Francesco P. J. Munson J. Garnier Sung-Hou Kim Jean-Michel Claverie Ian C. P. Smith P. T. Callaghan Bruce Cornell Ratna S. Phadke Kazuhiko Kinosita D. Goldfarb I. Qromov C. Shutter I. Pecht P. Manikandan R. Carmieli T. Shane David S. Moss Clare E. Sansom Jeremy K. Cockcroft Ian J. Tickle Huub C. P. Driessen J. Raul Grigera Ramen K. Poddar Charles R. Cantor Barry Robson Jean Garnier John Helliwell Sunney I. Chan Ronald Rock Physik-Department El7 Technische Universität München Garching Abteilung Biophysik Universität Ulm Ulm Advanced Science Research Center Japan Atomic Energy Research Institute Japan Laboratory of Chemical Physics NIDDK National Institutes of Health Bethesda USA National Lab of Biomacromolecules Institute of Biophysics Beijing China National Centre for Biological Sciences Bangalore Institute of Biophysical Chemistry University of Frankfurt Frankfurt/Main Germany Centre for Biomolecular Design and Drug Development University of Sussex UK Rutgers University Piscataway USA Department of Chemical Sciences Tata Institute of Fundamental Research Mumbai India IBMC-CNRS Strasbourg France Department of Biochemistry and Molecular Biology The University of Chicago Chicago USA Engelhardt Institute of Molecular Biology RAS Moscow Russia Sir William Dunn School of Pathology University of Oxford Oxford UK Structural Biology Center National Institute of Genetics Japan Faculty of Engineering Kyoto University Kyoto Advance Co. Tokyo Japan Department of Chemistry and Chemical Biology Cornell University Ithaca Institute de Biologie Structurale Joseph Fourier Grenoble Cedex 1 France Biomembrane Lab Department of Chemistry and Biotechnology CenterIndian Institute of Technology Bombay Powai Mumbai India Dept of Biomedical Sciences Univ. of Padova Italy Dept. Exp. Diagn. Med. Sect. Gen. Pathol Ferrara Italy Department of Biology University of California San Diego La Jolla USA Chinese Academy of Sciences Institute of Biophysics Beijing China Centra Nacional de Biotecnología CSIC. Campus de la Universidad Autónoma de Madrid Cantoblanco Spain Dept.of Biochemistry Bose Institute Calcutta-54 India The Scripps Research Institute La Jolla National Institute of Immunology New Delhi India Glycobiology Institute Department of Biochemistry University of Oxford Oxford UK Centre de Recherches sur les Macromolécules Végétales-CNRS Grenoble cedex 9 France Molecular Biophysics Uni

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