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Proceedings Paper

Feature extraction and image retrieval based on AlexNet
Author(s): Zheng-Wu Yuan; Jun Zhang
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Paper Abstract

Convolutional Neural Network is a hot research topic in image recognition. The latest research shows that Deep CNN model is good at extracting features and representing images. This capacity is applied to image retrieval in this paper. We study on the significance of each layer and do image retrieval experiments on the fusion features. Caffe framework and AlexNet model were used to extract the feature information about images. Two public image datasets, Inria Holidays and Oxford Buildings, were used in our experiment to search for the influence of different datasets. The results showed the fusion feature of Deep CNN model can improve the result of image retrieval and should apply different weights for different datasets.

Paper Details

Date Published: 29 August 2016
PDF: 5 pages
Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100330E (29 August 2016); doi: 10.1117/12.2243849
Show Author Affiliations
Zheng-Wu Yuan, Chongqing Univ. of Posts and Telecommunications (China)
Jun Zhang, Chongqing Univ. of Posts and Telecommunications (China)


Published in SPIE Proceedings Vol. 10033:
Eighth International Conference on Digital Image Processing (ICDIP 2016)
Charles M. Falco; Xudong Jiang, Editor(s)

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