Self-knowledge distillation enhanced binary neural networks derived from underutilized information
Author:
Funder
Yunnan Fundamental Research Projects
Major Science and Technology Projects in Yunnan Province
Talent Training Fund of Kunming University of Science and Technology
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10489-024-05444-8.pdf
Reference59 articles.
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3. Hong F, Kong L, Zhou H et al (2024) Unified 3d and 4d panoptic segmentation via dynamic shifting networks. IEEE Trans Pattern Anal Mach Intell 1–16. https://doi.org/10.1109/TPAMI.2023.3349304
4. Wang P, Chen W, He X et al (2023) Optimization-based post-training quantization with bit-split and stitching. IEEE Trans Pattern Anal Mach Intell 45(2):2119–2135. https://doi.org/10.1109/TPAMI.2022.3159369
5. Huang C, Liu P, Fang L (2021) MXQN: mixed quantization for reducing bit-width of weights and activations in deep convolutional neural networks. Appl Intell 51(7):4561–4574. https://doi.org/10.1007/s10489-020-02109-0
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