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RepMet: Representative-Based Metric Learning for Classification and Few-Shot Object Detection.

, , , , , , , and . CVPR, page 5197-5206. Computer Vision Foundation / IEEE, (2019)

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Detector-Free Weakly Supervised Grounding by Separation., , , , , , , , , and 7 other author(s). ICCV, page 1781-1792. IEEE, (2021)LaSO: Label-Set Operations Networks for Multi-Label Few-Shot Learning., , , , , , , and . CVPR, page 6548-6557. Computer Vision Foundation / IEEE, (2019)Delta-encoder: an effective sample synthesis method for few-shot object recognition., , , , , , , , and . NeurIPS, page 2850-2860. (2018)Sparsity-based Sinogram Denoising for low-dose Computed Tomography., , and . ICASSP, page 569-572. IEEE, (2011)Fine-Grained Recognition of Thousands of Object Categories with Single-Example Training., , , and . CVPR, page 965-974. IEEE Computer Society, (2017)NumeroLogic: Number Encoding for Enhanced LLMs' Numerical Reasoning., , , , , and . CoRR, (2024)StarNet: towards weakly supervised few-shot detection and explainable few-shot classification., , , , , , , , , and 1 other author(s). CoRR, (2020)Spatially-Adaptive Reconstruction in Computed Tomography using Neural Networks., , and . CoRR, (2013)StarNet: towards Weakly Supervised Few-Shot Object Detection., , , , , , , , , and 1 other author(s). AAAI, page 1743-1753. AAAI Press, (2021)Direct Adaptive Algorithms for CT Reconstruction., , and . ISBI, page 181-184. IEEE, (2009)