Art

J-GLOBAL ID：201902241816531987   Reference number：19A0958896

Development of Real-Time Screening System for Structural Surface Damage Using Object Detection and Generative Model Based on Deep Learning

深層学習に基づく物体検出と生成モデルを用いた構造表面損傷の実時間検出技術の開発

Author (2)： NOMURA YASUTOSHI (立命館大学大学院 理工学研究科) ,  SHIGEMURA KAZUKI (立命館大学大学院 理工学研究科)
Material： 材料  (Journal of the Society of Materials Science, Japan)
Volume： 68  Issue： 3  Page： 250-257(J-STAGE)  Publication year： 2019 
JST Material Number： F0385A  ISSN： 0514-5163  CODEN： ZARYA  Document type： Article
Article type： 原著論文  Country of issue： Japan (JPN)  Language： JAPANESE (JA)

Thesaurus term： *Machine Learning ,  structure (construction) ,  *damage and injury ,  *damage detection ,  neural network (biomodel) ,  crack ,  exfoliation ,  soundness ,  degradation (alteration) ,  learning data ,  *deep learning ,  *generation model ,  *surface damage ,  *object detection ,  *detection

Author keywords (1)： Deep convolution neural network Real-time object detection Concrete crack detection Concrete spalling detection Deep convolutional generative adversarial network

JST classification (1)： Structural mechanics in general  (HD01000X)

Reference (13)：

• 1) S. Nishimura, K. Hara, K. Kimoto and H. Matsuda, “The measurement and Draw damaged plans at Gunkan-Island by Using 3D laser scanner and Digital Camera”, Journal of Japan society of photogrammetry and remote sensing, Vol.51, No.1, pp.46-53, (2012).
• 2) S. Koyama, T. Maruya, K. Horiguchi and T. Sawa, “Digital image analysis of cracks on the concrete surface based on the Gabor wavelet transformation”, Journal of Japan society of civil engineers(E2), Vol.68, No.3, pp.178-194, (2012).
• 3) C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke and A. Rabinovich, “Going deeper with convolutions”, Proceedings of IEEE CVPR2015, (2015).
• 4) K. He, X. Zhang, S. Ren and J. Sun, “Spatial pyramid pooling in deep convolutional networks for visual recognition”, arXiv preprint arXiv:1406.4729v4, (2015).
• 5) S. Yokoyama and T. Matsumoto, ”Development of an automatic detector of surface damages in concrete using Deep Learning and the implementation of a web system”, Proc. of the 20^th Symposium on Applied Mechanics, pp.31-32, (2017).

Terms in the title (6)： 深層学習 ,  物体検出 ,  生成モデル ,  表面損傷 ,  実時間 ,  開発