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Author:

Liu, Zhengdong (Liu, Zhengdong.) | Liu, Yihan (Liu, Yihan.) | Wang, Shouren (Wang, Shouren.)

Indexed by:

EI PKU CSCD

Abstract:

In order to classify and detect the suit target in images of e-commerce platform accurately and quickly, an enhanced deep convolution network (DN-SSD) was proposed. First, three main frameworks faster region-convolutional networks (faster R-CNN), region-based fully convolution network(R-FCN) and single shot muti-box detection(SSD) were evaluated. An image was segmented into multiscale sub-images to highlight the suit target based on the SSD. Secondly, the problem of small target recognition was solved by the fusion of classification. The scene adaptability was enhanced by increasing number of negative samples. The experimental result shows that the algorithm can recognize various shapes and size of suit targets and achieves the accuracy over 90%. The method can also be generalized to other style of dress detection and location. Copyright No content may be reproduced or abridged without authorization.

Keyword:

Image enhancement Learning systems Deep neural networks Convolutional neural networks Target tracking Deep learning Convolution

Author Community:

  • [ 1 ] [Liu, Zhengdong]Fashion Accessory Art and Engineering College, Beijing Institute of Fashion Technology, Beijing; 100029, China
  • [ 2 ] [Liu, Yihan]Information Department, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Wang, Shouren]College of Computer Science and Electronic Engineering, Hunan University, Changsha; Hunan; 410082, China

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Source :

Journal of Textile Research

ISSN: 0253-9721

Year: 2019

Issue: 4

Volume: 40

Page: 158-164

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 5

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 17

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