Laser & Optoelectronics Progress, Volume. 55, Issue 11, 111007(2018)

A Pedestrian Detection Method Based on Dark Channel Defogging and Deep Learning

Qing Tian1, Tongyang Yuan1、*, Dan Yang1, and Yun Wei2
Author Affiliations
  • 1 School of Electronic Information Engineering, North China University of Technology, Beijing 100144, China
  • 2 Beijing Urban Construction Design & Development Group Co., Ltd., Beijing 100037, China;
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    References(11)

    [1] Sermanet P, Kavukcuoglu K, Chintala S et al. Pedestrian detection with unsupervised multi-stage feature learning. [C]∥Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 3626-3633(2013).

    [3] LeCun Y, Bengio Y, Hinton G. Deep learning[J]. Nature, 521, 436-444(2015).

    [8] Gupta S, Girshick R, Arbeláez P et al. Learning rich features from RGB-D images for object detection and segmentation. [C]∥European Conference on Computer Vision, 345-360(2014).

    [10] Wang K, Dong Y, Bai H L et al. Use fast R-CNN and cascade structure for face detection. [C]∥Visual Communications and Image Processing (VCIP), 1-4(2016).

    [11] Eggert C, Brehm S, Winschel A et al. A closer look: small object detection in faster R-CNN. [C]∥IEEE International Conference on Multimedia and Expo (ICME), 421-426(2017).

    CLP Journals

    [1] Huan Liu, Chungeng Li, Jubai An, Guo Wei, Junli Ren. Multiple Object Tracking Based on Kernelized Correlation Filter[J]. Laser & Optoelectronics Progress, 2019, 56(12): 121501

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    Qing Tian, Tongyang Yuan, Dan Yang, Yun Wei. A Pedestrian Detection Method Based on Dark Channel Defogging and Deep Learning[J]. Laser & Optoelectronics Progress, 2018, 55(11): 111007

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    Paper Information

    Category: Image Processing

    Received: Apr. 16, 2018

    Accepted: May. 29, 2018

    Published Online: Aug. 14, 2019

    The Author Email: Tongyang Yuan (2017311020137@mail.ncut.edu.cn)

    DOI:10.3788/LOP55.111007

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