| Automatic detection method of cracks from concrete surface imagery using two‐step light gradient boosting machine P Chun, S Izumi, T Yamane Computer‐Aided Civil and Infrastructure Engineering 36 (1), 61-72, 2021 | 208 | 2021 |
| Random forest-based evaluation technique for internal damage in reinforced concrete featuring multiple nondestructive testing results P Chun, I Ujike, K Mishima, M Kusumoto, S Okazaki Construction and Building Materials 253, 119238, 2020 | 96 | 2020 |
| A deep learning‐based image captioning method to automatically generate comprehensive explanations of bridge damage PJ Chun, T Yamane, Y Maemura Computer‐Aided Civil and Infrastructure Engineering 37 (11), 1387-1401, 2022 | 95 | 2022 |
| Crack detection from a concrete surface image based on semantic segmentation using deep learning T Yamane, P Chun Journal of Advanced Concrete Technology 18 (9), 493-504, 2020 | 92 | 2020 |
| Applicability of machine learning to a crack model in concrete bridges Y Okazaki, S Okazaki, S Asamoto, P Chun Computer‐Aided Civil and Infrastructure Engineering 35 (8), 775-792, 2020 | 80 | 2020 |
| Bridge damage severity quantification using multipoint acceleration measurement and artificial neural networks P Chun, H Yamashita, S Furukawa Shock and Vibration 2015 (1), 789384, 2015 | 68 | 2015 |
| Automatic detection of cracks in asphalt pavement using deep learning to overcome weaknesses in images and GIS visualization P Chun, T Yamane, Y Tsuzuki Applied Sciences 11 (3), 892, 2021 | 52 | 2021 |
| Evaluation of tensile performance of steel members by analysis of corroded steel surface using deep learning P Chun, T Yamane, S Izumi, T Kameda Metals 9 (12), 1259, 2019 | 52 | 2019 |
| Tensile strength prediction of corroded steel plates by using machine learning approach CN Karina, PJ Chun, K Okubo Steel Compos. Struct 24 (5), 635-641, 2017 | 52 | 2017 |
| ディープラーニングおよび Random Forest によるコンクリートのひび割れ自動検出手法 全邦釘， 嶋本ゆり， 大窪和明， 三輪知寛， 大賀水田生 土木学会論文集 F3 (土木情報学) 73 (2), I_297-I_307, 2017 | 50 | 2017 |
| Development of a machine learning-based damage identification method using multi-point simultaneous acceleration measurement results P Chun, T Yamane, S Izumi, N Kuramoto Sensors 20 (10), 2780, 2020 | 44 | 2020 |
| Innovative technologies for infrastructure construction and maintenance through collaborative robots based on an open design approach K Nagatani, M Abe, K Osuka, P Chun, T Okatani, M Nishio, S Chikushi, ... Advanced Robotics 35 (11), 715-722, 2021 | 42 | 2021 |
| Artificial neural network for vertical displacement prediction of a bridge from strains (Part 1): Girder bridge under moving vehicles HS Moon, S Ok, P Chun, YM Lim Applied Sciences 9 (14), 2881, 2019 | 40 | 2019 |
| Random forest によるコンクリート表面ひび割れの検出 全邦釘， 井後敦史 土木学会論文集 F3 (土木情報学) 71 (2), I_1-I_8, 2015 | 38 | 2015 |
| Utilization of unmanned aerial vehicle, artificial intelligence, and remote measurement technology for bridge inspections P Chun, J Dang, S Hamasaki, R Yajima, T Kameda, H Wada, T Yamane, ... Journal of Robotics and Mechatronics 32 (6), 1244-1258, 2020 | 37 | 2020 |
| Development of a concrete floating and delamination detection system using infrared thermography P Chun, S Hayashi IEEE/ASME Transactions on Mechatronics 26 (6), 2835-2844, 2021 | 35 | 2021 |
| 車載カメラにより撮影された舗装画像からのディープラーニングによるひび割れ率評価 全邦釘， 井後敦史， 南免羅裕治， 黒木航汰， 大窪和明 土木学会論文集 E1 (舗装工学) 73 (3), I_97-I_105, 2017 | 34 | 2017 |
| Deep learningによるSemantic Segmentationを用いたコンクリート表面ひび割れの検出 邦釘山根 達郎，全 構造工学論文集 65 (A), 130-138, 2019 | 31 | 2019 |
| Recording of bridge damage areas by 3D integration of multiple images and reduction of the variability in detected results T Yamane, P Chun, J Dang, R Honda Computer‐Aided Civil and Infrastructure Engineering 38 (17), 2391-2407, 2023 | 28 | 2023 |
| Asphalt pavement crack detection using image processing and naive bayes based machine learning approach P Chun, K HASHIMOTO, N KATAOKA, N KURAMOTO, M OHGA Journal of Japan Society of Civil Engineers, Ser. E1 (Pavement Engineering …, 2015 | 26 | 2015 |
Tatsuro YamaneNational Institute of Technology, Tokuyama College在 tokuyama.ac.jp 的电子邮件经过验证
