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cs.CV2024★ 1 cited
Test-time Adaptation Meets Image Enhancement: Improving Accuracy via Uncertainty-aware Logit Switching
Shohei Enomoto, Naoya Hasegawa, Kazuki Adachi +4
Deep neural networks have achieved remarkable success in a variety of computer vision applications. However, there is a problem of degrading accuracy when the data distribution shi…
cs.CV2023
Incorporating Supervised Domain Generalization into Data Augmentation
Shohei Enomoto, Monikka Roslianna Busto, Takeharu Eda
With the increasing utilization of deep learning in outdoor settings, its robustness needs to be enhanced to preserve accuracy in the face of distribution shifts, such as compressi…