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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…
cs.CV2022
Dynamic Test-Time Augmentation via Differentiable Functions
Shohei Enomoto, Monikka Roslianna Busto, Takeharu Eda
Distribution shifts, which often occur in the real world, degrade the accuracy of deep learning systems, and thus improving robustness to distribution shifts is essential for pract…