Incorporating Supervised Domain Generalization into Data Augmentation

no code implementations • 2 Oct 2023 • 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 compression artifacts.

Data Augmentation Domain Generalization

Dynamic Test-Time Augmentation via Differentiable Functions

no code implementations • 9 Dec 2022 • Shohei Enomoto, Monikka Roslianna Busto, Takeharu Eda

We propose a novel image enhancement method, DynTTA, which is based on differentiable data augmentation techniques and generates a blended image from many augmented images to improve the recognition accuracy under distribution shifts.

Classification Data Augmentation +1