| Titre : | The impact of the new image compression scheme JPEG AI on image analysis tasks |
| Auteurs : | Mohamed Riadh Temmar, Auteur ; Sid-Ahmed Berrani, Directeur de thèse ; Jean-Luc Dugelay, Directeur de thèse |
| Type de document : | document électronique |
| Editeur : | [S.l.] : [s.n.], 2023 |
| Format : | 1 fichier PDF (25 Mo) / ill. |
| Note générale : |
Mode d'accès : accès au texte intégral par intranet.
Mémoire de Projet de Fin d’Etudes : Electronique : Alger, Ecole Nationale Polytechnique : 2023 Bibliogr. P. 90 - 92 |
| Langues : | Anglais |
| Index. décimale : | PN00223 |
| Tags : | Artificial intelligence Computer vision Face recognition Image compression Image processing |
| 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. |
Exemplaires (1)
| Cote | Support | Localisation | Section | Disponibilité | Spécialité | Etat_Exemplaire |
|---|---|---|---|---|---|---|
| PN00223 | Ressources électroniques | Bibliothèque centrale | Projet Fin d'Etudes | Disponible | Electronique | Téléchargeable |
Documents numériques (1)
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TEMMAR.Mohamed-Riadh.pdf URL
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