Mohamed AKIL

About

Mohamed Akil received his PhD degree from Montpellier University (France) in 1981 and his doctorat d’état (DSc) from the Pierre et Marie curie University (UPMC, Paris, France) in 1985. Since September 1985, he has been with ESIEE Paris that is the CCIR’s (Chambre de commerce et d'industrie de région Paris Ile-de-France) center for scientific and engineering education and research. He was Professor in the Computer Science Department, ESIEE Paris from 1985 to 2017. He is Professor Emeritus from 2017. He is Doctor Honoris Causa of the University of West Bohemia.


He is a membrer of the Laboratoire d’Informatique Gaspard Monge, Université Gustave Eiffel (UMR 8049, unité mixte de recherche CNRS), a joint research laboratory between Université Paris-Est Marne-la-Vallée (UPEM), ESIEE Paris and École des Ponts ParisTech (ENPC). He is member of the program committee of the SPIE - Real Time Image and Video Processing conference (RTIVP). He is member of the Editorial Board of the Journal of Real-Time Processing (JRTIP). His research interests include dedicated and parallel architectures for image processing, Real-Time implementation on embedded processors and Smartphone platforms. His main research topics are parallel and dedicated architectures for real time image processing, parallel architectures (Multicore, GPUs). His current areas focus on machine learning and deep learning in medicine (ocular pathologies, brain tumor segmentation. He has published more than 160 research papers in the above areas. He supervised to completion more than twenty fourPhD students.

Employment

• Université Gustave Eiffel Professor Emeritus
  2018 - Present

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (140)

• Automated method for real-time AMD screening of fundus images dedicated for mobile devices
  Medical and Biological Engineering and Computing 2022 DOI: 10.1007/s11517-022-02546-8
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• Tuning Image Descriptors and Classifiers: The Case of Emotion Recognition
  Lecture Notes in Electrical Engineering 2022 DOI: 10.1007/978-981-33-6893-4_80
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• A Fast and Accurate Method for Glaucoma Screening from Smartphone-Captured Fundus Images
  IRBM 2021 DOI: 10.1016/j.irbm.2021.06.004
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• Detection of retinal abnormalities in fundus image using CNN deep learning networks
  State of the Art in Neural Networks and Their Applications: Volume 1 2021 DOI: 10.1016/B978-0-12-819740-0.00002-4
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• Fast and efficient retinal blood vessel segmentation method based on deep learning network
  Computerized Medical Imaging and Graphics 2021 DOI: 10.1016/j.compmedimag.2021.101902
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• Mobile-aided screening system for proliferative diabetic retinopathy
  International Journal of Imaging Systems and Technology 2021 DOI: 10.1002/ima.22547
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• A deep learning-based smartphone app for real-time detection of five stages of diabetic retinopathy
  Proceedings of SPIE - The International Society for Optical Engineering 2020 DOI: 10.1117/12.2557554
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• A new pipeline for the recognition of universal expressions of multiple faces in a video sequence
  Journal of Real-Time Image Processing 2020 DOI: 10.1007/s11554-019-00896-5
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• Computational aspects of deep learning models for detection of eye retina abnormalities
  Proceedings of SPIE - The International Society for Optical Engineering 2020 DOI: 10.1117/12.2557601
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• Deep convolutional neural networks for brain tumor segmentation: Boosting performance using deep transfer learning: Preliminary results
  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2020 DOI: 10.1007/978-3-030-46643-5_30
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