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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| Weighted Linear Discriminant Analysis based on Class Saliency Information |
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| Lei Xu, Alexandros Iosifidis, Moncef Gabbouj |
| 2018 |
| arxiv 1802.06547 |
| Deep Learning For Computer Vision Tasks: A review | Rajat Kumar Sinha, Ruchi Pandey, Rohan Pattnaik | 2018 | arxiv 1804.03928 |
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| Optical Neural Networks | Grant Fennessy, Yevgeniy Vorobeychik | 2018 | arxiv 1805.06082 |
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| Maximal Jacobian-based Saliency Map Attack | Rey Wiyatno, Anqi Xu | 2018 | arxiv 1808.07945 |
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| Deep Neural Networks for Pattern Recognition | Kyongsik Yun, Alexander Huyen, Thomas Lu | 2018 | arxiv 1809.09645 |
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| Analysis Dictionary Learning: An Efficient and Discriminative Solution | Wen Tang, Ashkan Panahi, Hamid Krim | 2019 | arxiv 1903.03058 |
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| WeNet: Weighted Networks for Recurrent Network Architecture Search | Zhiheng Huang, Bing Xiang | 2019 | arxiv 1904.03819 |
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| DARTS: Differentiable Architecture Search | Hanxiao Liu, Karen Simonyan, Yiming Yang | 2018 | arxiv 1806.09055 |
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| Simultaneously Learning Architectures and Features of Deep Neural Networks | Tinghuai Wang, Lixin Fan, Huiling Wang | 2019 | arxiv 1906.04505 |
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| Explanatory Masks for Neural Network Interpretability | Lawrence Phillips, Garrett Goh, Nathan Hodas | 2019 | arxiv 1911.06876 |
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