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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| Remus Pop, Patric Fulop |
| 2018 |
| arxiv 1811.03897 |
| Are pre-trained CNNs good feature extractors for anomaly detection in surveillance videos? | Tiago S. Nazare, Rodrigo F. de Mello, Moacir A. Ponti | 2018 | arxiv 1811.08495 |
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| Adversarial Attacks for Optical Flow-Based Action Recognition Classifiers | Nathan Inkawhich, Matthew Inkawhich, Yiran Chen | 2018 | arxiv 1811.11875 |
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| Unsupervised Domain Adaptation using Regularized Hyper-graph Matching | Debasmit Das, C.S. George Lee | 2018 | arxiv 1805.08874 |
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| Toward Multimodal Model-Agnostic Meta-Learning | Risto Vuorio, Shao-Hua Sun, Hexiang Hu | 2018 | arxiv 1812.07172 |
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| Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images | Bruno Lecouat, Ken Chang, Chuan-Sheng Foo | 2018 | arxiv 1812.07832 |
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| Learning Compressed Transforms with Low Displacement Rank | Anna T. Thomas, Albert Gu, Tri Dao | 2018 | arxiv 1810.02309 |
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| On Minimum Discrepancy Estimation for Deep Domain Adaptation | Mohammad Mahfujur Rahman, Clinton Fookes, Mahsa Baktashmotlagh | 2019 | arxiv 1901.00282 |
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| A Push-Pull Layer Improves Robustness of Convolutional Neural Networks | Nicola Strisciuglio, Manuel Lopez-Antequera, Nicolai Petkov | 2019 | arxiv 1901.10208 |
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| Prototype-based Neural Network Layers: Incorporating Vector Quantization | Sascha Saralajew, Lars Holdijk, Maike Rees | 2018 | arxiv 1812.01214 |
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