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DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition.

, , , , , , and . ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 647-655. JMLR.org, (2014)

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Annotator rationales for visual recognition., and . ICCV, page 1395-1402. IEEE Computer Society, (2011)Semi-supervised Domain Adaptation with Instance Constraints., , , , and . CVPR, page 668-675. IEEE Computer Society, (2013)Asymmetric and Category Invariant Feature Transformations for Domain Adaptation., , , , and . Int. J. Comput. Vis., 109 (1-2): 28-41 (2014)Large Scale Adversarial Representation Learning., and . NeurIPS, page 10541-10551. (2019)LSDA: Large Scale Detection through Adaptation., , , , , , , and . NIPS, page 3536-3544. (2014)Training Generative Adversarial Networks by Solving Ordinary Differential Equations., , , , , , and . NeurIPS, (2020)Region-Based Convolutional Networks for Accurate Object Detection and Segmentation., , , and . IEEE Trans. Pattern Anal. Mach. Intell., 38 (1): 142-158 (2016)Large Scale GAN Training for High Fidelity Natural Image Synthesis., , and . ICLR, OpenReview.net, (2019)LOGAN: Latent Optimisation for Generative Adversarial Networks., , , , and . CoRR, (2019)Translating Videos to Natural Language Using Deep Recurrent Neural Networks., , , , , and . HLT-NAACL, page 1494-1504. The Association for Computational Linguistics, (2015)