Joint weighted knowledge distillation and multi-scale feature distillation for long-tailed recognition-Reference-Cited by-同舟云学术

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Joint weighted knowledge distillation and multi-scale feature distillation for long-tailed recognition

Published:2023-11-01 Issue: Volume: Page:
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

He Yiru,Wang Shiqian,Yu Junyang^ORCID,Liu Chaoyang,He Xin,Li Han

Funder

the Key Science and Technology Project of Henan Province

Henan Provincial Science and Technology Research Project

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s13042-023-01988-2.pdf

Reference51 articles.

1. Zhu X, Men J, Yang L et al (2022) Imbalanced driving scene recognition with class focal loss and data augmentation. Int J Mach Learn Cybern 13(10):2957–2975. https://doi.org/10.1007/s13042-022-01575-x

2. Zhao Z, Zuo M, Yu J et al (2022) Siamese network based on global and local feature matching for object tracking. J Electron Imaging 31:063,022-063,022. https://doi.org/10.1117/1.JEI.31.6.063022

3. Han M, Guo H, Li J et al (2022) Global-local information based oversampling for multi-class imbalanced data. Int J Mach Learn Cybern. https://doi.org/10.1007/s13042-022-01746-w

4. Everingham M, Van Gool L, Williams CK et al (2009) The pascal visual object classes (voc) challenge. Int J Comput Vision 88:303–308. https://doi.org/10.1007/s11263-009-0275-4

5. Deng J, Dong W, Socher R et al (2009) Imagenet: a large-scale hierarchical image database. In: 2009 IEEE conference on computer vision and pattern recognition. Ieee, pp 248–255. https://doi.org/10.1109/CVPR.2009.5206848

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