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cs.CV2025
Dropout Prompt Learning: Towards Robust and Adaptive Vision-Language Models
Biao Chen, Lin Zuo, Mengmeng Jing +2
Dropout is a widely used regularization technique which improves the generalization ability of a model by randomly dropping neurons. In light of this, we propose Dropout Prompt Lea…
cs.CV2025
A Semantic-Enhanced Heterogeneous Graph Learning Method for Flexible Objects Recognition
Kunshan Yang, Wenwei Luo, Yuguo Hu +3
Flexible objects recognition remains a significant challenge due to its inherently diverse shapes and sizes, translucent attributes, and subtle inter-class differences. Graph-based…
cs.CV2025
SWAT: Sliding Window Adversarial Training for Gradual Domain Adaptation
Zixi Wang, Xiangxu Zhao, Tonglan Xie +2
Domain shifts are critical issues that harm the performance of machine learning. Unsupervised Domain Adaptation (UDA) mitigates this issue but suffers when the domain shifts are st…