Automatic detection method of cracks from concrete surface imagery using two‐step light gradient boosting machine von Chun, Pang‐jo, Izumi, Shota, Yamane, Tatsuro

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A deep learning‐based image captioning method to automatically generate comprehensive explanations of bridge damage von Chun, Pang‐Jo, Yamane, Tatsuro, Maemura, Yu

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Crack Detection from a Concrete Surface Image Based on Semantic Segmentation Using Deep Learning von Yamane, Tatsuro, Chun, Pang-jo

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Development of a Concrete Floating and Delamination Detection System Using Infrared Thermography von Chun, Pang-jo, Hayashi, Shogo

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Fine‐grained crack segmentation for high‐resolution images via a multiscale cascaded network von Chu, Honghu, Chun, Pang‐jo

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Applicability of machine learning to a crack model in concrete bridges von Okazaki, Yuriko, Okazaki, Shinichiro, Asamoto, Shingo, Chun, Pang‐jo

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Recording of bridge damage areas by 3D integration of multiple images and reduction of the variability in detected results von Yamane, Tatsuro, Chun, Pang‐jo, Dang, Ji, Honda, Riki

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Improving visual question answering for bridge inspection by pre‐training with external data of image–text pairs von Kunlamai, Thannarot, Yamane, Tatsuro, Suganuma, Masanori, Chun, Pang‐Jo, Okatani, Takayaki

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Study on Accuracy Improvement of Slope Failure Region Detection Using Mask R-CNN with Augmentation Method von Kubo, Shiori, Yamane, Tatsuro, Chun, Pang-Jo

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Random forest-based evaluation technique for internal damage in reinforced concrete featuring multiple nondestructive testing results von Chun, Pang-jo, Ujike, Isao, Mishima, Kohei, Kusumoto, Masahiro, Okazaki, Shinichiro

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Cascade refinement extraction network with active boundary loss for segmentation of concrete cracks from high-resolution images von Deng, Lu, Yuan, Huaqing, Long, Lizhi, Chun, Pang-jo, Chen, Weiwei, Chu, Honghu

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ViTALnet: Anomaly on Industrial Textured Surfaces With Hybrid Transformer von Tao, Xian, Adak, Chandranath, Chun, Pang-Jo, Yan, Shaohua, Liu, Huaping

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Development of a Machine Learning-Based Damage Identification Method Using Multi-Point Simultaneous Acceleration Measurement Results von Chun, Pang-jo, Yamane, Tatsuro, Izumi, Shota, Kuramoto, Naoya

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Self‐training with Bayesian neural networks and spatial priors for unsupervised domain adaptation in crack segmentation von Chun, Pang‐jo, Kikuta, Toshiya

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Welcome From the New Editor-in-Chief von Pang, Ai-Chun

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Energy-Aware 3D Unmanned Aerial Vehicle Deployment for Network Throughput Optimization von Chou, Shih-Fan, Pang, Ai-Chun, Yu, Ya-Ju

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Automatic Detection of Cracks in Asphalt Pavement Using Deep Learning to Overcome Weaknesses in Images and GIS Visualization von Chun, Pang-jo, Yamane, Tatsuro, Tsuzuki, Yukino

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Periodontal disease and emotional disorders: A meta‐analysis von Zheng, De‐Xiu, Kang, Xiao‐Ning, Wang, Yi‐Xi, Huang, Yi‐Na, Pang, Chun‐Feng, Chen, Yu‐Xuan, Kuang, Zhi‐Li, Peng, Yun

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Battery state of health modeling and remaining useful life prediction through time series model von Lin, Chun-Pang, Cabrera, Javier, Yang, Fangfang, Ling, Man-Ho, Tsui, Kwok-Leung, Bae, Suk-Joo

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Recycled waste black polyurethane sponges for solar vapor generation and distillation von Ma, Sainan, Chiu, Chun Pang, Zhu, Yujiao, Tang, Chun Yin, Long, Hui, Qarony, Wayesh, Zhao, Xinhua, Zhang, Xuming, Lo, Wai Hung, Tsang, Yuen Hong

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