Pang-jo Chun

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Tatsuro YamaneNational Institute of Technology, Tokuyama CollegeVerified email at tokuyama.ac.jp
Shota IzumiKajima CorporationVerified email at kajima.com
Ji DangSaitama University, Civil and Environment Engineering, Strucutral Mechanic and Dynamic Group.Verified email at mail.saitama-u.ac.jp
Ranjith DissanayakeProfessor of Civil Engineering, University of PeradeniyaVerified email at fulbrightmail.org
Yun Mook LimProfessor, Civil Engineering, Yonsei UniversityVerified email at yonsei.ac.kr
Shingo AsamotoSaitama UniversityVerified email at mail.saitama-u.ac.jp
Shinichiro OkazakiKagawa UniversityVerified email at eng.kagawa-u.ac.jp
J.M.R.S. AppuhamyFaculty of Engineering, University of RuhunaVerified email at is.ruh.ac.lk
Okatani TakayukiProfessor, Graduate School of Information Sciences, Tohoku University / RIKEN Center for AIPVerified email at vision.is.tohoku.ac.jp
Keiji NagataniProfessor of Mechanical Engineering, Tohoku UniversityVerified email at ieee.org
Yuriko OkazakiKagawa UniversityVerified email at kagawa-u.ac.jp
Y MaemuraDepartment of International Studies, The University of TokyoVerified email at g.ecc.u-tokyo.ac.jp
Toshihiro KamedaUniversity of TsukubaVerified email at kz.tsukuba.ac.jp
Hajime AsamaUniversity of TokyoVerified email at robot.t.u-tokyo.ac.jp
Mayuko NISHIOUniversity of TsukubaVerified email at kz.tsukuba.ac.jp
Honghu ChuHunan University; University College LondonVerified email at hnu.edu.cn
Yusuke IkemotoMeijo UniversityVerified email at meijo-u.ac.jp
Takamitsu MatsubaraProfessor, Nara Institute of Science and TechnologyVerified email at is.naist.jp
xian taoInstitute of Automation, Chinese Academy of SciencesVerified email at ia.ac.cn
Huaping LiuProfessor of Electrical Engineering, Oregon State UniversityVerified email at oregonstate.edu

Pang-jo Chun

Other names全　邦釘, BANGJO CHUN, BANJO CHUN

The University of Tokyo

Verified email at i-con.t.u-tokyo.ac.jp - Homepage

Bridge Engineering Maintenance Artificial Intelligence Image Processing


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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	212	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	97	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	93	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	81	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	54	2021
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	53	2017
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
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	45	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	41	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	36	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	32	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
Iterative application of generative adversarial networks for improved buried pipe detection from images obtained by ground‐penetrating radar PJ Chun, M Suzuki, Y Kato Computer‐Aided Civil and Infrastructure Engineering 38 (17), 2472-2490, 2023	27	2023

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