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Interpretable Compositional Representations for Robust Few-Shot Generalization.

, , и . IEEE Trans. Pattern Anal. Mach. Intell., 46 (3): 1496-1512 (марта 2024)

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Dushyant Mishra

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VisDA-2021 Competition Universal Domain Adaptation to Improve Performance on Out-of-Distribution Data., , , , , , , и . CoRR, (2021)VisDA-2021 Competition: Universal Domain Adaptation to Improve Performance on Out-of-Distribution Data., , , , , , , , , и 1 other автор(ы). NeurIPS (Competition and Demos), том 176 из Proceedings of Machine Learning Research, стр. 66-79. PMLR, (2021)VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sorting., , , , , , , , , и 9 other автор(ы). NeurIPS (Competition and Demos), том 220 из Proceedings of Machine Learning Research, стр. 104-118. PMLR, (2021)Effectively Leveraging Attributes for Visual Similarity., , , , , и . CVPR Workshops, стр. 3904-3909. Computer Vision Foundation / IEEE, (2021)A novel hybrid approach for automated detection of retinal detachment using ultrasound images., , , , , , , , и . Comput. Biol. Medicine, (2020)Learning Compositional Representations for Effective Low-Shot Generalization., , и . CoRR, (2022)Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency., , и . BMVC, стр. 177. BMVA Press, (2021)SynCDR : Training Cross Domain Retrieval Models with Synthetic Data., , и . CoRR, (2024)Fine-grained Few-shot Recognition by Deep Object Parsing., , , и . CoRR, (2022)Low Dimensional Visual Attributes: An Interpretable Image Encoding., , , и . ICPR Workshops (3), том 12663 из Lecture Notes in Computer Science, стр. 90-102. Springer, (2020)