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Please use this identifier to cite or link to this item: https://repository.esi-sba.dz/jspui/handle/123456789/379
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dc.contributor.authorBELLAOUEDJ, ISmail-
dc.date.accessioned2022-11-14T07:26:23Z-
dc.date.available2022-11-14T07:26:23Z-
dc.date.issued2022-
dc.identifier.urihttps://repository.esi-sba.dz/jspui/handle/123456789/379-
dc.descriptionEncadreur : Mr HADJILA Fethallah Co-Encadreur : Mr AMAR BENSABER Djamelen_US
dc.description.abstractCurrently, several studies are discussing the detection of lung diseases by analyzing medical images using deep learning. Deep learning is also a valuable aid to experts in the interpretation of medical images. Heuristics such as transfer learning (a deep learning method where a model developed for a given task is reused as a starting point for another model that targets a second task) is emerging. These approaches (based on pre-trained models) are used as the starting point for computer vision tasks and can offer considerable gains to many problems. In this manuscript, we going to review recent researches that implement Convolutional Neural Networks (CNN) models to detect the presence of COVID-19 in X-ray images. *** Actuellement, plusieurs ´etudes discutent la d´etection des maladies pulmonaires en analysant images m´edicales en exploitant l’apprentissage profond (deep learning).Ce dernier constitue aussi une aide pr´ecieuse aux experts pour l’interpr´etation des images m´edicales. Des heuristiques telles que l’apprentissage par transfert(une m´ethode d’apprentissage profond o`u un mod`ele d´evelopp´e pour une tˆache est r´eutilis´e comme point de d´epart d’un mod`ele sur une seconde tˆache) est en train d’´emerger. Ces approches `a base de mod`eles pr´e-entraˆın´es sont utilis´es comme le point de d´epart des tˆaches de vision par ordinateur et peuvent leur assurer d’ ´enormes gains. Dans ce manuscrit, nous allons passer en revue les recherches r´ecentes qui mettent en oeuvre des mod`eles de r´eseaux neuronaux convolutifs (CNN) pour d´etecter la pr´esence de COVID-19 dans les images radiologiques.en_US
dc.language.isoenen_US
dc.subjectDeep Learningen_US
dc.subjectConvolutional Neural Networksen_US
dc.subjectCovid-19 Detectionen_US
dc.subjectTransfer Learning Transferen_US
dc.titleD´etection du COVID-19 par r´eseaux convolutionnels et `a l’aide des images radiologiques (X-rays)en_US
dc.typeThesisen_US
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