Optimized Feature Space Learning for Generating Efficient Binary Codes for Image Retrieval

In this paper we propose an approach for learning low dimensional optimized feature space with minimum intra-class variance and maximum inter-class variance. We address the problem of high-dimensionality of feature vectors extracted from neural networks by taking care of the global statistics of feature space... (read more)

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