| Road damage detection and classification using deep neural networks with smartphone images H Maeda, Y Sekimoto, T Seto, T Kashiyama, H Omata Computer‐Aided Civil and Infrastructure Engineering 33 (12), 1127-1141, 2018 | 739 | 2018 |
| Road damage detection using deep neural networks with images captured through a smartphone H Maeda, Y Sekimoto, T Seto, T Kashiyama, H Omata arXiv preprint arXiv:1801.09454, 2018 | 296 | 2018 |
| Generative adversarial network for road damage detection H Maeda, T Kashiyama, Y Sekimoto, T Seto, H Omata Computer‐Aided Civil and Infrastructure Engineering 36 (1), 47-60, 2021 | 278 | 2021 |
| Deep learning-based road damage detection and classification for multiple countries D Arya, H Maeda, SK Ghosh, D Toshniwal, A Mraz, T Kashiyama, ... Automation in Construction 132, 103935, 2021 | 190 | 2021 |
| Global road damage detection: State-of-the-art solutions D Arya, H Maeda, SK Ghosh, D Toshniwal, H Omata, T Kashiyama, ... 2020 IEEE International Conference on Big Data (Big Data), 5533-5539, 2020 | 168 | 2020 |
| Transfer learning-based road damage detection for multiple countries D Arya, H Maeda, SK Ghosh, D Toshniwal, A Mraz, T Kashiyama, ... arXiv preprint arXiv:2008.13101, 2020 | 118 | 2020 |
| Open PFLOW: Creation and evaluation of an open dataset for typical people mass movement in urban areas T Kashiyama, Y Pang, Y Sekimoto Transportation research part C: emerging technologies 85, 249-267, 2017 | 54 | 2017 |
| Crowdsensing-based road damage detection challenge (CRDDC’2022) D Arya, H Maeda, SK Ghosh, D Toshniwal, H Omata, T Kashiyama, ... 2022 IEEE international conference on big data (big data), 6378-6386, 2022 | 47 | 2022 |
| Deep reinforcement learning approach for train rescheduling utilizing graph theory M Obara, T Kashiyama, Y Sekimoto 2018 IEEE International Conference on Big Data (Big Data), 4525-4533, 2018 | 47 | 2018 |
| Particle filter for real-time human mobility prediction following unprecedented disaster A Sudo, T Kashiyama, T Yabe, H Kanasugi, X Song, T Higuchi, S Nakano, ... Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances …, 2016 | 37 | 2016 |
| Development of people mass movement simulation framework based on reinforcement learning Y Pang, T Kashiyama, T Yabe, K Tsubouchi, Y Sekimoto Transportation research part C: emerging technologies 117, 102706, 2020 | 25 | 2020 |
| Real-time people movement estimation in large disasters from several kinds of mobile phone data Y Sekimoto, A Sudo, T Kashiyama, T Seto, H Hayashi, A Asahara, ... Proceedings of the 2016 ACM International Joint Conference on Pervasive and …, 2016 | 24 | 2016 |
| Real-time citywide reconstruction of traffic flow from moving cameras on lightweight edge devices A Kumar, T Kashiyama, H Maeda, H Omata, Y Sekimoto ISPRS Journal of Photogrammetry and Remote Sensing 192, 115-129, 2022 | 22 | 2022 |
| Rdd2020: an image dataset for smartphone-based road damage detection and classification D Arya, H Maeda, SK Ghosh, D Toshniwal, H Omata, T Kashiyama, T Seto, ... Mendel. Data 1, 2021 | 22 | 2021 |
| Road damage detection using deep neural networks with images captured through a smartphone. arXiv 2018 H Maeda, Y Sekimoto, T Seto, T Kashiyama, H Omata arXiv preprint arXiv:1801.09454, 2018 | 21 | 2018 |
| Citywide reconstruction of cross-sectional traffic flow from moving camera videos A Kumar, T Kashiyama, H Maeda, Y Sekimoto 2021 IEEE International Conference on Big Data (Big Data), 1670-1678, 2021 | 17 | 2021 |
| RDD2022-The multi-national Road Damage Dataset released through CRDDC'2022 D Arya, H Maeda, Y Sekimoto, H Omata, SK Ghosh, D Toshniwal, ... (No Title), 2022 | 16 | 2022 |
| Sky monitoring system for flying object detection using 4K resolution camera T Kashiyama, H Sobue, Y Sekimoto Sensors 20 (24), 7071, 2020 | 16 | 2020 |
| Transportation melting pot Dhaka: road-link based traffic volume estimation from sparse CDR data Y Hasegawa, Y Sekimoto, T Kashiyama, H Kanasugi Proceedings of the First International Conference on IoT in Urban Space, 105-107, 2014 | 14 | 2014 |
| Pseudo-pflow: Development of nationwide synthetic open dataset for people movement based on limited travel survey and open statistical data T Kashiyama, Y Pang, Y Sekimoto, T Yabe arXiv preprint arXiv:2205.00657, 2022 | 11 | 2022 |
