Feature extraction and image retrieval based on AlexNet

Zheng-Wu Yuan; Jun Zhang

doi:10.1117/12.2243849

29 August 2016 Feature extraction and image retrieval based on AlexNet

Zheng-Wu Yuan, Jun Zhang

Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 100330E (2016) https://doi.org/10.1117/12.2243849
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China

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.

Citation Download Citation

Zheng-Wu Yuan and Jun Zhang "Feature extraction and image retrieval based on AlexNet", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100330E (29 August 2016); https://doi.org/10.1117/12.2243849

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