Art
J-GLOBAL ID:202002222323092779   Reference number:20A1827785

Object Detection through Modified YOLO Neural Network

修正YOLOニューラルネットワークによるオブジェクト検出【JST・京大機械翻訳】
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Volume: 2020  Page: Null  Publication year: 2020 
JST Material Number: W0689A  ISSN: 1058-9244  Document type: Article
Article type: 原著論文  Country of issue: United Kingdom (GBR)  Language: ENGLISH (EN)
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In the field of object detecti...
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Graphic and image processing in general 
Reference (42):
  • A. Tiwari, A. Kumar, G. M. Saraswat, "Feature extraction for object recognition and image classification," International Journal of Engineering Research & Technology (IJERT), vol. 2, pp. 2278-0181, 2013.
  • J. Yan, Z. Lei, L. Wen, S. Z. Li, "The fastest deformable part model for object detection," Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2497-2504, New York, NY, USA, 2014.
  • T. Dean, M. A. Ruzon, M. Segal, J. Shlens, S. Vijayanarasimhan, J. Yagnik, "Fast, accurate detection of 100,000 object classes on a single machine," Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1814-1821, New York, NY, USA, 2013.
  • P. Viola, M. J. Jones, "Robust real-time face detection," International Journal of Computer Vision, vol. 57, no. 2, pp. 137-154, 2004.
  • C.-J. Du, H.-J. He, D.-W. Sun, "Object classification methods," Computer Vision Technology for Food Quality Evaluation, pp. 87-110, Elsevier, Berlin, Germany, 2016.
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