Deep Learning based Model for Prohibited Goods Detection
- 10.2991/asei-15.2015.23How to use a DOI?
- Prohibited goods; Deep Convolutional Neural Networks; Deep Belief Networks
With the rapid development of Internet technology, massive images are used on e-commerce sites to show product details. Among those images there are some of contraband, which seriously harm the social harmony, thus it is important to automatically identify them. In this paper, we propose an effective method aims at solving this problem, in contrast with traditional methods, we do not use human designed visual features and classification models, but combine deep features and deep learning model. Experiment results show that our method outperform previous human designed features and visual models tremendously.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Zhao Liu AU - Ying Ruan AU - Chun Chen PY - 2015/05 DA - 2015/05 TI - Deep Learning based Model for Prohibited Goods Detection BT - Proceedings of the 2015 International conference on Applied Science and Engineering Innovation PB - Atlantis Press SP - 103 EP - 106 SN - 2352-5401 UR - https://doi.org/10.2991/asei-15.2015.23 DO - 10.2991/asei-15.2015.23 ID - Liu2015/05 ER -