Veuillez utiliser cette adresse pour citer ce document : http://repository.enp.edu.dz/jspui/handle/123456789/10781
Titre: The impact of the new image compression scheme JPEG AI on image analysis tasks
Auteur(s): Temmar, Mohamed Riadh
Berrani, Sid-Ahmed, Directeur de thèse
Dugelay, Jean-Luc, Directeur de thèse
Mots-clés: Artificial intelligence
Image compression
Face recognition
Image processing
Computer vision
Date de publication: 2023
Résumé: Image compression plays a vital role in storing and transmitting digital media. In addition to traditional compression methods, there have been recent advancements in AI-based techniques. These methods are designed with specific objectives in mind, such as optimized image reconstruction or utilizing latent representations for computer vision tasks. In this study, we explore the variations among these AI-based codecs based on their objectives by tackling a classification problem. following that we focuses on creating an enhanced image compressor capable of performing three tasks: image compression, computer vision, and image processing. Specifically, we chose face recognition and resolution doubling as secondary tasks alongside image compression.
Description: Mémoire de Projet de Fin d’Études : Electronique : Alger, École Nationale Polytechnique : 2023
URI/URL: http://repository.enp.edu.dz/jspui/handle/123456789/10781
Collection(s) :Département Electronique

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