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Updated: Feb 6, 2026

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning
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动态双向数据重组,以实现半监督学习中的有效道路垃圾细分

Suheng Peng1, Jiacai Liao2, Libo Cao1

  • 1School of Mechanical and Vehicle Engineering, Hunan University, Lushan South Road, Yuelu District, Changsha, Hunan Province, Changsha, 410082, Hunan, China.

Neural networks : the official journal of the International Neural Network Society
|February 4, 2026
PubMed
概括

本研究介绍了动态双向数据复制 (DBDR) 以提高使用半监督学习 (SSL) 的道路垃圾细分. DBDR通过动态平衡标记和未标记数据来提高模型性能,克服城市废物管理中的注释限制.

关键词:
深度学习是一种深度学习.垃圾分类垃圾分类语义细分 语义细分是指语义细分.半监督学习 半监督学习

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