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insight - Contrastive Learning Framework
Probabilistic Representation Contrastive Learning for Semi-Supervised Semantic Segmentation
The author proposes a Probabilistic Representation Contrastive Learning (PRCL) framework to enhance the robustness of unsupervised training in semi-supervised semantic segmentation by introducing probabilistic representations and global distribution prototypes.
PRCL: Probabilistic Representation Contrastive Learning for Semi-Supervised Semantic Segmentation
提案されたPRCLフレームワークは、半教師ありセマンティックセグメンテーションにおけるロバストな対照学習プロセスを向上させます。
CLHA: A Simple yet Effective Contrastive Learning Framework for Human Alignment
簡単で効果的な対照学習フレームワークを使用して、大規模言語モデルを人間の適合性に整える。
Contrastive Learning for Regression on Hyperspectral Data
Contrastive learning improves regression on hyperspectral data.
PRCL: Probabilistic Representation Contrastive Learning for Semi-Supervised Semantic Segmentation
효율적인 반지도 학습을 위한 확률적 표현 대조 학습 프레임워크
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