Learning semantic ambiguities for zero-shot learning
CC BY
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| Tác giả chính: | , |
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| Định dạng: | Sách |
| Ngôn ngữ: | English |
| Nhà xuất bản: |
Springer
2023
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| Truy cập trực tuyến: | https://link.springer.com/article/10.1007/s11042-023-14877-1 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7403 |
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oai:localhost:PNK-74032023-03-31T09:26:09Z Learning semantic ambiguities for zero-shot learning Celina, Hanouti Hervé Le, Borgne Zero-shot learning synthesize visual features CC BY Zero-shot learning (ZSL) aims at recognizing classes for which no visual sample is available at training time. To address this issue, one can rely on a semantic description of each class. A typical ZSL model learns a mapping between the visual samples of seen classes and the corresponding semantic descriptions, in order to do the same on unseen classes at test time. State of the art approaches rely on generative models that synthesize visual features from the prototype of a class, such that a classifier can then be learned in a supervised manner. However, these approaches are usually biased towards seen classes whose visual instances are the only one that can be matched to a given class prototype. 2023-03-31T09:26:09Z 2023-03-31T09:26:09Z 2023 Book https://link.springer.com/article/10.1007/s11042-023-14877-1 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7403 en application/pdf Springer |
| institution |
Digital Phenikaa |
| collection |
Digital Phenikaa |
| language |
English |
| topic |
Zero-shot learning synthesize visual features |
| spellingShingle |
Zero-shot learning synthesize visual features Celina, Hanouti Hervé Le, Borgne Learning semantic ambiguities for zero-shot learning |
| description |
CC BY |
| format |
Book |
| author |
Celina, Hanouti Hervé Le, Borgne |
| author_facet |
Celina, Hanouti Hervé Le, Borgne |
| author_sort |
Celina, Hanouti |
| title |
Learning semantic ambiguities for zero-shot learning |
| title_short |
Learning semantic ambiguities for zero-shot learning |
| title_full |
Learning semantic ambiguities for zero-shot learning |
| title_fullStr |
Learning semantic ambiguities for zero-shot learning |
| title_full_unstemmed |
Learning semantic ambiguities for zero-shot learning |
| title_sort |
learning semantic ambiguities for zero-shot learning |
| publisher |
Springer |
| publishDate |
2023 |
| url |
https://link.springer.com/article/10.1007/s11042-023-14877-1 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7403 |
| _version_ |
1761912528071294976 |
| score |
8.891145 |