Thanks to the success of deep learning, hashing has recently evolved as a leading method for large-scale image retrieval. Most existing methods use last layer extract semantic information from input image. However, these have deficiencies because features extracted lack local information, which might impact global system’s performance. To this end, Deep Feature Pyramid Hashing DFPH is proposed ...

Driven by the urgent demand of remote sensing big data management and knowledge discovery, large-scale remote sensing image retrieval (LSRSIR) has attracted more and more attention. As is well known, hashing learning has played an important role in coping with big data mining problems. In the literature, several hashing learning methods have been proposed to address LSRSIR. Until now, existing ...

This paper introduces a hashing based framework that facilitates sketch based image retrieval in large image databases. Instead of exporting a single visual descriptor for every image, an overlapping spatial grid is utilised to generate a pool of patches. We rank similarities between a hand drawn sketch and the natural images in a database through a voting process where near duplicate in terms ...

Recent studies show that large-scale sketch-based image retrieval (SBIR) can be efficiently tackled by cross-modal binary representation learning methods, where Hamming distance matching significantly speeds up the process of similarity search. Providing training and test data subjected to a fixed set of pre-defined categories, the cutting-edge SBIR and cross-modal hashing works obtain acceptab...

In order to make the speech perception hashing authentication algorithm has strong robustness and discrimination to content preserving operations and speech communication under the common background noise, a new robust speech perceptual hashing authentication algorithm based on spectral subtraction and multi-feature tensor was proposed. The proposed algorithm uses spectral subtraction method to...