Internet cross-media retrieval based on deep learning
journal contributionposted on 24.03.2017 by Bin Jiang, Jiachen Yang, Zhihan Lv, Kun Tian, Qinggang Meng, Yan Yan
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With the development of Internet, multimedia information such as image and video is widely used. Therefore, how to find the required multimedia data quickly and accurately in a large number of resources , has become a research focus in the field of information process. In this paper, we propose a real time internet cross-media retrieval method based on deep learning. As an innovation, we have made full improvement in feature extracting and distance detection. After getting a large amount of image feature vectors, we sort the elements in the vector according to their contribution and then eliminate unnecessary features. Experiments show that our method can achieve high precision in image-text cross media retrieval, using less retrieval time. This method has a great application space in the field of cross media retrieval.
This research is partially supported by National Natural Science Foundation of China (No. 61471260 and No. 61271324), and Natural Science Foundation of Tianjin (No. 16JCYBJC16000).
- Computer Science