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cs.CV2024
ERUP-YOLO: Enhancing Object Detection Robustness for Adverse Weather Condition by Unified Image-Adaptive Processing
Yuka Ogino, Yuho Shoji, Takahiro Toizumi +1
We propose an image-adaptive object detection method for adverse weather conditions such as fog and low-light. Our framework employs differentiable preprocessing filters to perform…
cs.CV2024
Adaptive Deep Iris Feature Extractor at Arbitrary Resolutions
Yuho Shoji, Yuka Ogino, Takahiro Toizumi +1
This paper proposes a deep feature extractor for iris recognition at arbitrary resolutions. Resolution degradation reduces the recognition performance of deep learning models train…
cs.CV2024
Improving Low-Light Image Recognition Performance Based on Image-adaptive Learnable Module
Seitaro Ono, Yuka Ogino, Takahiro Toizumi +2
In recent years, significant progress has been made in image recognition technology based on deep neural networks. However, improving recognition performance under low-light condit…