| The simplest measurement matrix for compressed sensing of natural images Z He, T Ogawa, M Haseyama 2010 IEEE International Conference on Image Processing, 4301-4304, 2010 | 76 | 2010 |
| [Survey paper] a review of video retrieval based on image and video semantic understanding M Haseyama, T Ogawa, N Yagi ITE Transactions on Media Technology and Applications 1 (1), 2-9, 2013 | 49 | 2013 |
| Convolutional sparse coding‐based deep random vector functional link network for distress classification of road structures K Maeda, S Takahashi, T Ogawa, M Haseyama Computer‐Aided Civil and Infrastructure Engineering 34 (8), 654-676, 2019 | 47 | 2019 |
| Image inpainting based on sparse representations with a perceptual metric T Ogawa, M Haseyama EURASIP Journal on Advances in Signal Processing 2013, 1-26, 2013 | 46 | 2013 |
| Cardiac sarcoidosis classification with deep convolutional neural network-based features using polar maps R Togo, K Hirata, O Manabe, H Ohira, I Tsujino, K Magota, T Ogawa, ... Computers in biology and medicine 104, 81-86, 2019 | 41 | 2019 |
| Detection of gastritis by a deep convolutional neural network from double-contrast upper gastrointestinal barium X-ray radiography R Togo, N Yamamichi, K Mabe, Y Takahashi, C Takeuchi, M Kato, ... Journal of gastroenterology 54, 321-329, 2019 | 40 | 2019 |
| Missing intensity interpolation using a kernel PCA-based POCS algorithm and its applications T Ogawa, M Haseyama IEEE Transactions on Image Processing 20 (2), 417-432, 2010 | 40 | 2010 |
| Favorite video classification based on multimodal bidirectional LSTM T Ogawa, Y Sasaka, K Maeda, M Haseyama IEEE Access 6, 61401-61409, 2018 | 39 | 2018 |
| A cross-modal approach for extracting semantic relationships between concepts using tagged images M Katsurai, T Ogawa, M Haseyama IEEE transactions on multimedia 16 (4), 1059-1074, 2014 | 37 | 2014 |
| Soft-label anonymous gastric x-ray image distillation G Li, R Togo, T Ogawa, M Haseyama 2020 IEEE International Conference on Image Processing (ICIP), 305-309, 2020 | 33 | 2020 |
| Estimation of deterioration levels of transmission towers via deep learning maximizing canonical correlation between heterogeneous features K Maeda, S Takahashi, T Ogawa, M Haseyama IEEE journal of selected topics in signal processing 12 (4), 633-644, 2018 | 28 | 2018 |
| Missing image data reconstruction based on adaptive inverse projection via sparse representation T Ogawa, M Haseyama IEEE Transactions on Multimedia 13 (5), 974-992, 2011 | 28 | 2011 |
| Compressed gastric image generation based on soft-label dataset distillation for medical data sharing G Li, R Togo, T Ogawa, M Haseyama Computer Methods and Programs in Biomedicine 227, 107189, 2022 | 27 | 2022 |
| Synthetic gastritis image generation via loss function-based conditional pggan R Togo, T Ogawa, M Haseyama IEEE access 7, 87448-87457, 2019 | 26 | 2019 |
| Land use in habitats affects metal concentrations in wild lizards around a former lead mining site R Doya, SMM Nakayama, H Nakata, H Toyomaki, J Yabe, K Muzandu, ... Environmental science & technology 54 (22), 14474-14481, 2020 | 24 | 2020 |
| Preliminary study of AI-assisted diagnosis using FDG-PET/CT for axillary lymph node metastasis in patients with breast cancer Z Li, K Kitajima, K Hirata, R Togo, J Takenaka, Y Miyoshi, K Kudo, ... EJNMMI research 11, 1-10, 2021 | 23 | 2021 |
| Novel audio feature projection using KDLPCCA-based correlation with EEG features for favorite music classification R Sawata, T Ogawa, M Haseyama IEEE transactions on affective computing 10 (3), 430-444, 2017 | 23 | 2017 |
| Detection of gastric cancer risk from X-ray images via patch-based convolutional neural network K Ishihara, T Ogawa, M Haseyama 2017 IEEE International Conference on Image Processing (ICIP), 2055-2059, 2017 | 22 | 2017 |
| Self-knowledge distillation based self-supervised learning for covid-19 detection from chest x-ray images G Li, R Togo, T Ogawa, M Haseyama ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 21 | 2022 |
| Team tactics estimation in soccer videos based on a deep extreme learning machine and characteristics of the tactics G Suzuki, S Takahashi, T Ogawa, M Haseyama Ieee Access 7, 153238-153248, 2019 | 21 | 2019 |
Miki HaseyamaHokkaido UniversityVerified email at ist.hokudai.ac.jp
