Applicability of machine learning to a crack model in concrete bridges. - Yuriko Okazaki; Shinichiro Okazaki; Shingo Asamoto; Pang-jo Chun (Comput. Aided Civ. Infrastructure Eng., 2020)

Utilization of Unmanned Aerial Vehicle, Artificial Intelligence, and Remote Measurement Technology for Bridge Inspections. - Pang-jo Chun; Ji Dang; Shunsuke Hamasaki; Ryosuke Yajima; Toshihiro Kameda; Hideki Wada; Tatsuro Yamane; Shota Izumi; Keiji Nagatani (J. Robotics Mechatronics, 2020)

Development of a Machine Learning-Based Damage Identification Method Using Multi-Point Simultaneous Acceleration Measurement Results. - Pang-jo Chun; Tatsuro Yamane; Shota Izumi; Naoya Kuramoto (Sensors, 2020)

Innovative technologies for infrastructure construction and maintenance through collaborative robots based on an open design approach. - Keiji Nagatani; Masato Abe; Koichi Osuka; Pang-jo Chun; Takayuki Okatani; Mayuko Nishio; Shota Chikushi; Takamitsu Matsubara; Yusuke Ikemoto; Hajime Asama (Adv. Robotics, 2021)

Development of an excavator-avoidance system for buried pipes. - Ryosuke Yajima; Shinya Katsuma; Makoto Suzuki; Fumiya Matsushita; Shunsuke Hamasaki; Pang-jo Chun; Keiji Nagatani; Genki Yamauchi; Takeshi Hashimoto; Atsushi Yamashita; Hajime Asama; Kazumasa Ozawa (Adv. Robotics, 2021)

Automatic detection method of cracks from concrete surface imagery using two-step light gradient boosting machine. - Pang-jo Chun; Shota Izumi; Tatsuro Yamane (Comput. Aided Civ. Infrastructure Eng., 2021)

A deep learning-based image captioning method to automatically generate comprehensive explanations of bridge damage. - Pang-jo Chun; Tatsuro Yamane; Yu Maemura (Comput. Aided Civ. Infrastructure Eng., 2022)

Study on Accuracy Improvement of Slope Failure Region Detection Using Mask R-CNN with Augmentation Method. - Shiori Kubo; Tatsuro Yamane; Pang-jo Chun (Sensors, 2022)

Bridge Damage Cause Estimation Using Multiple Images Based on Visual Question Answering. - Tatsuro Yamane; Pang-jo Chun; Ji Dang; Takayuki Okatani (CoRR, 2023)

ViTALnet: Anomaly on Industrial Textured Surfaces With Hybrid Transformer. - Xian Tao; Chandranath Adak; Pang-jo Chun; Shaohua Yan; Huaping Liu 001 (IEEE Trans. Instrum. Meas., 2023)

Iterative application of generative adversarial networks for improved buried pipe detection from images obtained by ground-penetrating radar. - Pang-jo Chun; M. Suzuki; Y. Kato (Comput. Aided Civ. Infrastructure Eng., 2023)

Recording of bridge damage areas by 3D integration of multiple images and reduction of the variability in detected results. - Tatsuro Yamane; Pang-jo Chun; Ji Dang; Riki Honda (Comput. Aided Civ. Infrastructure Eng., 2023)

Implementation of explanatory texts output for bridge damage in a bridge inspection web system. - Pang-jo Chun; Honghu Chu; Kota Shitara; Tatsuro Yamane; Yu Maemura (Adv. Eng. Softw., 2024)

Fine-grained crack segmentation for high-resolution images via a multiscale cascaded network. - Honghu Chu; Pang-jo Chun (Comput. Aided Civ. Infrastructure Eng., 2024)

Improving visual question answering for bridge inspection by pre-training with external data of image-text pairs. - Thannarot Kunlamai; Tatsuro Yamane; Masanori Suganuma; Pang-jo Chun; Takayuki Okatani (Comput. Aided Civ. Infrastructure Eng., 2024)

Development of an action classification method for construction sites combining pose assessment and object proximity evaluation. - Toshiya Kikuta; Pang-jo Chun (J. Ambient Intell. Humaniz. Comput., 2024)

Self-training with Bayesian neural networks and spatial priors for unsupervised domain adaptation in crack segmentation. - Pang-jo Chun; Toshiya Kikuta (Comput. Aided Civ. Infrastructure Eng., 2024)

A structure-oriented loss function for automated semantic segmentation of bridge point clouds. - Chao Lin; Shuhei Abe; Shitao Zheng; Xianfeng Li; Pang-jo Chun (Comput. Aided Civ. Infrastructure Eng., 2025)