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J-GLOBAL ID:201902257256006803   Reference number:19A0898139

Cross-Domain Change Object Detection Using Generative Adversarial Networks

敵対的生成ネットワークを用いたクロスドメイン変化物体検出
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Volume: 31  Issue:Page: 221-230  Publication year: Apr. 20, 2019 
JST Material Number: L0735A  ISSN: 0915-3942  Document type: Article
Article type: 原著論文  Country of issue: Japan (JPN)  Language: ENGLISH (EN)
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Pattern recognition  ,  Artificial intelligence 
Reference (32):
  • [1] D. W. van de Wouw, G. Dubbelman, and P. H. de With, “Hierarchical 2.5-d scene alignment for change detection with large viewpoint differences,” IEEE Robotics and Automation Letters, Vol.1, No.1, pp. 361-368, 2016.
  • [2] B. Mathias, D. Marcin, G. Igor, C. Cesar, S. Roland, and N. Juan, “Map management for efficient long-term visual localization in outdoor environments,” Proc. of 2018 IEEE Intelligent Vehicles Symp. (IV), pp. 682-688, 2018.
  • [3] R. J. Radke, S. Andra, O. Al-Kofahi, and B. Roysam, “Image change detection algorithms: a systematic survey,” IEEE Trans. on Image Processing, Vol.14, No.3, pp. 294-307, 2005.
  • [4] R. Finman, T. Whelan, M. Kaess, and J. J. Leonard, “Toward lifelong object segmentation from change detection in dense rgb-d maps,” 2013 European Conf. on Mobile Robots (ECMR), pp. 178-185, 2013.
  • [5] K. Kim, T. H. Chalidabhongse, D. Harwood, and L. Davis, “Background modeling and subtraction by codebook construction,” 2004 Int. Conf. on Image Processing (ICIP’04), pp. 3061-3064, 2004.
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