| 2025 | ICIP | Curve: Clip-Utilized Reinforcement Learning for Visual Image Enhancement via Simple Image Processing. | Yuka Ogino, Takahiro Toizumi, Atsushi Ito |
| 2025 | ICIP | Rethinking Image Histogram Matching for Image Classification. | Rikuto Otsuka, Yuho Shoji, Yuka Ogino, Takahiro Toizumi, Atsushi Ito |
| 2025 | ICIP | Target Driven Adaptive Loss for Infrared Small Target Detection. | Yuho Shoji, Takahiro Toizumi, Atsushi Ito |
| 2025 | WACV | ERUP-YOLO: Enhancing Object Detection Robustness for Adverse Weather Condition by Unified Image-Adaptive Processing. | Yuka Ogino, Yuho Shoji, Takahiro Toizumi, Atsushi Ito |
| 2025 | VISIGRAPP | Recognition-Oriented Low-Light Image Enhancement Based on Global and Pixelwise Optimization. | Seitaro Ono, Yuka Ogino, Takahiro Toizumi, Atsushi Ito, Masato Tsukada |
| 2024 | CVPR | Outsmarting Biometric Imposters: Enhancing Iris-Recognition System Security through Physical Adversarial Example Generation and PAD Fine-Tuning. | Yuka Ogino, Kazuya Kakizaki, Takahiro Toizumi, Atsushi Ito |
| 2024 | VISIGRAPP | Improving Low-Light Image Recognition Performance Based on Image-Adaptive Learnable Module. | Seitaro Ono, Yuka Ogino, Takahiro Toizumi, Atsushi Ito, Masato Tsukada |
| 2023 | WACV | Segmentation-free Direct Iris Localization Networks. | Takahiro Toizumi, Koichi Takahashi, Masato Tsukada |
| 2021 | IGARSS | Inter-Orbit Change Detection for High-Resolution SAR Imagery Using Conditional Siamese Network. | Eiji Kaneko, Takahiro Toizumi, Kazutoshi Sagi, Masato Toda |
| 2019 | ICIP | Artifact-Free Thin Cloud Removal Using Gans. | Takahiro Toizumi, Simone Zini, Kazutoshi Sagi, Eiji Kaneko, Masato Tsukada, Raimondo Schettini |
| 2018 | ICONIP | Central Pattern Generator Based on Interstitial Cell Models Made from Bursting Neuron Models. | Takahiro Toizumi, Katsutoshi Saeki |
| 2018 | IGARSS | Rollable Latent Space for Azimuth Invariant Sar Target Recognition. | Kazutoshi Sagi, Takahiro Toizumi, Yuzo Senda |
| 2018 | IGARSS | Automatic Association between Sar and Optical Images based on Zero-Shot Learning. | Takahiro Toizumi, Kazutoshi Sagi, Yuzo Senda |