Mol2text
| dc.contributor.author | Mihoubi, Houssem | |
| dc.contributor.author | Yesseri, Marwa | |
| dc.contributor.author | Hentabli, Hamza | |
| dc.date.accessioned | 2023-01-18T09:11:32Z | |
| dc.date.available | 2023-01-18T09:11:32Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | In recent years, automatic image annotation (AIA) has become an emerging research topic aiming at reducing human labeling efforts for large-scale image collections . AIA refers to the process of automatically labeling the images with a predefined set of keywords or concepts representing image semantics .the aim of AIA is to build associations between image visual contents and concepts ;the aim of this reserach is to develop a novel method of Automatic Molecules annotaion MOL2text ,based on deep learning graph neural network (GNN) ,to build associations between molecules structure and concepts of key word | fr |
| dc.identifier.citation | Ingénierie de Systèmes et Technologies de Web | fr |
| dc.identifier.govdoc | M622223 | |
| dc.identifier.uri | https://dspace.univ-medea.dz/handle/123456789/7670 | |
| dc.language.iso | en | fr |
| dc.relation.ispartofseries | ;M622223 | |
| dc.subject | Molecular description | fr |
| dc.subject | deep learning | fr |
| dc.subject | Automatic image annotation | fr |
| dc.title | Mol2text | fr |
| dc.title.alternative | Automatic Molecular Description Using Deep Learning | fr |
| dc.type | Thesis | fr |
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