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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| Does progress on ImageNet transfer to real-world datasets? |
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| Alex Fang, Simon Kornblith, Ludwig Schmidt |
| 2023 |
| arxiv 2301.04644 |
| MMViT: Multiscale Multiview Vision Transformers | Yuchen Liu, Natasha Ong, Kaiyan Peng | 2023 | arxiv 2305.00104 |
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| A Melting Pot of Evolution and Learning | Moshe Sipper, Achiya Elyasaf, Tomer Halperin | 2023 | arxiv 2306.04971 |
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| Context Augmentation for Convolutional Neural Networks | Aysegul Dundar, Ignacio Garcia-Dorado | 2017 | arxiv 1712.01653 |
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| Semi-supervised Fisher vector network | Petar Palasek, Ioannis Patras | 2018 | arxiv 1801.04438 |
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| Gradient Normalization & Depth Based Decay For Deep Learning | Robert Kwiatkowski, Oscar Chang | 2017 | arxiv 1712.03607 |
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| Improving Whole Slide Segmentation Through Visual Context - A Systematic Study | Korsuk Sirinukunwattana, Nasullah Khalid Alham, Clare Verrill | 2018 | arxiv 1806.04259 |
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| Fine-Tuning VGG Neural Network For Fine-grained State Recognition of Food Images | Kaoutar Ben Ahmed, Ahmad Babaeian Jelodar | 2018 | arxiv 1809.09529 |
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| Semantic bottleneck for computer vision tasks | Maxime Bucher, Stéphane Herbin, Frédéric Jurie | 2018 | arxiv 1811.02234 |
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| Spatial Correlation and Value Prediction in Convolutional Neural Networks | Gil Shomron, Uri Weiser | 2018 | arxiv 1807.10598 |
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