From text saliency to linguistic objects: learning linguistic interpretable markers with a multi-channels convolutional architecture
A lot of effort is currently made to provide methods to analyze and understand deep neural network impressive performances for tasks such as image or text classification. These methods are mainly based on visualizing the important input features taken into account by the network to build a decision....
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| Publicat a: | URI:https://journals.openedition.org/corpus, |
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| Autors principals: | , , , |
| Format: | Article ou chapitre numérique |
| Idioma: | Anglais |
| Publicat: |
Corpus
2023
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| Matèries: | |
| Accés en línia: | Accès Université d'Orléans et IFPM Accès Université d'Orléans et IFPM |