| Leafgan: An effective data augmentation method for practical plant disease diagnosis QH Cap, H Uga, S Kagiwada, H Iyatomi IEEE Transactions on Automation Science and Engineering 19 (2), 1258-1267, 2020 | 128 | 2020 |
| A deep learning approach for on-site plant leaf detection HQ Cap, K Suwa, E Fujita, S Kagiwada, H Uga, H Iyatomi 2018 IEEE 14th International Colloquium on Signal Processing & Its …, 2018 | 56 | 2018 |
| Aop: An anti-overfitting pretreatment for practical image-based plant diagnosis T Saikawa, QH Cap, S Kagiwada, H Uga, H Iyatomi 2019 IEEE International Conference on Big Data (Big Data), 5177-5182, 2019 | 27 | 2019 |
| LASSR: Effective super-resolution method for plant disease diagnosis QH Cap, H Tani, S Kagiwada, H Uga, H Iyatomi Computers and Electronics in Agriculture 187, 106271, 2021 | 24 | 2021 |
| A comparable study: Intrinsic difficulties of practical plant diagnosis from wide-angle images K Suwa, QH Cap, R Kotani, H Uga, S Kagiwada, H Iyatomi 2019 IEEE International Conference on Big Data (Big Data), 5195-5201, 2019 | 19 | 2019 |
| Super-resolution for practical automated plant disease diagnosis system QH Cap, H Tani, H Uga, S Kagiwada, H Iyatomi 2019 53rd Annual Conference on Information Sciences and Systems (CISS), 1-6, 2019 | 18 | 2019 |
| An End-To-End Practical Plant Disease Diagnosis System for Wide-Angle Cucumber Images QH Cap, K Suwa, E Fujita, S Kagiwada, H Uga, H Iyatomi International Journal of Engineering & Technology 7 (4.11), 106-111, 2018 | 17 | 2018 |
| Validation of prerequisites for correct performance evaluation of image-based plant disease diagnosis using reliable 221K images collected from actual fields S Shibuya, QH Cap, S Nagasawa, S Kagiwada, H Uga, H Iyatomi AI for Agriculture and Food Systems, 2022 | 8 | 2022 |
| PPIG: Productive and pathogenic image generation for plant disease diagnosis S Kanno, S Nagasawa, QH Cap, S Shibuya, H Uga, S Kagiwada, ... 2020 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES …, 2021 | 6 | 2021 |
| Towards Robust Plant Disease Diagnosis with Hard-sample Re-mining Strategy QH Cap, A Fukuda, S Kagiwada, H Uga, N Iwasaki, H Iyatomi Computers and Electronics in Agriculture 215, 108375, 2023 | 3 | 2023 |
| Stochastic Gastric Image Augmentation for Cancer Detection from X-ray Images H Okamoto, QH Cap, T Nomura, H Iyatomi, J Hashimoto 2019 IEEE International Conference on Big Data (Big Data), 4858-4863, 2019 | 3 | 2019 |
| A Practical Framework for Unsupervised Structure Preservation Medical Image Enhancement QH Cap, A Fukuda, H Iyatomi arXiv preprint arXiv:2304.01864, 2023 | 1 | 2023 |
| Key Area Acquisition Training for Practical Image-based Plant Disease Diagnosis K Odagiri, S Shibuya, QH Cap, H Iyatomi 2022 IEEE 18th International Colloquium on Signal Processing & Applications …, 2022 | 1 | 2022 |
| MIINet: An Image Quality Improvement Framework for Supporting Medical Diagnosis QH Cap, H Iyatomi, A Fukuda Pattern Recognition. ICPR International Workshops and Challenges: Virtual …, 2021 | 1 | 2021 |
| High-Quality Medical Image Generation from Free-hand Sketch QH Cap, A Fukuda arXiv preprint arXiv:2402.00353, 2024 | | 2024 |
| Bulk Production Augmentation Towards Explainable Melanoma Diagnosis K Obi, QH Cap, N Umegaki-Arao, M Tanaka, H Iyatomi 2020 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES …, 2021 | | 2021 |
| An End-To-End Practical Plant Disease Diagnosis System For Wide-Angle Cucumber Images QH Cap, H Iyatomi 法政大学大学院紀要. 理工学・工学研究科編, 1-6, 2019 | | 2019 |
| A basic study on leaves detection with deep learning features HQ CAP, E Fujita, K Suwa, S Kagiwada, H Uga, H Iyatomi IEICE Conferences Archives, 2017 | | 2017 |
| Super-Resolution for Practical Automated Diseases Diagnosis System QH Cap, H Tani, H Uga, S Kagiwada, H Iyatomi | | |
Hitoshi IyatomiProfessor, Hosei University, JapanVerified email at hosei.ac.jp
Hitoshi IyatomiProfessor, Hosei University, JapanVerified email at hosei.ac.jp