6 papers
IA-CLAHE: Image-Adaptive Clip Limit Estimation for CLAHE
Rikuto Otsuka, Yuho Shoji, Yuka Ogino +2
This paper proposes image-adaptive contrast limited adaptive histogram equalization (IA-CLAHE). Conventional CLAHE is widely used to boost the performance of various computer visio…
Target Driven Adaptive Loss For Infrared Small Target Detection
Yuho Shoji, Takahiro Toizumi, Atsushi Ito
We propose a target driven adaptive (TDA) loss to enhance the performance of infrared small target detection (IRSTD). Prior works have used loss functions, such as binary cross-ent…
Rethinking Image Histogram Matching for Image Classification
Rikuto Otsuka, Yuho Shoji, Yuka Ogino +2
This paper rethinks image histogram matching (HM) and proposes a differentiable and parametric HM preprocessing for a downstream classifier. Convolutional neural networks have demo…
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…
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…
Fast Eye Detector Using Siamese Network for NIR Partial Face Images
Yuka Ogino, Yuho Shoji, Takahiro Toizumi +2
This paper proposes a fast eye detection method that is based on a Siamese network for near infrared (NIR) partial face images. NIR partial face images do not include the whole fac…