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Object and Text-guided Semantics for CNN-based Activity Recognition.

, , , , and . ICASSP, page 1458-1462. IEEE, (2019)

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Progressive Transformation Learning for Leveraging Virtual Images in Training., , , and . CVPR, page 835-844. IEEE, (2023)Object and Text-guided Semantics for CNN-based Activity Recognition., , , , and . ICASSP, page 1458-1462. IEEE, (2019)Kernel RX-algorithm: a nonlinear anomaly detector for hyperspectral imagery., and . IEEE Trans. Geosci. Remote. Sens., 43 (2): 388-397 (2005)Coalition game theory based feature subset selection for hyperspectral image classification., and . IGARSS, page 3446-3449. IEEE, (2014)Contextual SVM for hyperspectral classification using Hilbert Space Embedding., and . IGARSS, page 5470-5473. IEEE, (2012)Unsupervised segmentation algorithm based on an iterative spectral dissimilarity measure for hyperspectral imagery., , and . VCIP, volume 4310 of Proceedings of SPIE, page 144-152. SPIE, (2001)Optimal kernel bandwidth estimation for hyperspectral kernel-based anomaly detection., and . IGARSS, page 2812-2815. IEEE, (2010)EDIR: Efficient Distributed Image Retrieval of Novel Objects in Mobile Networks., , , and . MASS, page 392-400. IEEE, (2021)Shapely value based random subspace selection for hyperspectral image classification., , and . IGARSS, page 4975-4978. IEEE, (2015)Coalition Game Theory-Based Feature Subspace Selection for Hyperspectral Classification., , and . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 9 (6): 2354-2364 (2016)