Pang-jo Chun

According to our database, Pang-jo Chun authored at least 14 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

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., February, 2024

Fine-grained crack segmentation for high-resolution images via a multiscale cascaded network.

Honghu Chu, Pang-jo Chun

Comput. Aided Civ. Infrastructure Eng., February, 2024

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., November, 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., November, 2023

ViTALnet: Anomaly on Industrial Textured Surfaces With Hybrid Transformer.

Xian Tao, Chandranath Adak, Pang-jo Chun, Shaohua Yan, Huaping Liu

IEEE Trans. Instrum. Meas., 2023

Bridge Damage Cause Estimation Using Multiple Images Based on Visual Question Answering.

Tatsuro Yamane, Pang-jo Chun, Ji Dang, Takayuki Okatani

CoRR, 2023

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

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

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

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

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

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

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

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