Hashing algorithm has attracted great attention in recent years. In order to improve the query
speed and retrieval accuracy, this paper proposes an adaptive and asymmetric residual …

Hashing has been widely used for large-scale image retrieval due to its high storage
efficiency and fast calculation speed. Recent works have found that deep-supervised …

Currently, due to the exponential growth of online images, it is necessary to consider image
retrieval among large number of images, which is very time-consuming and unscalable …

Recently, deep learning to hash has extensively been applied to image retrieval, due to its
low storage cost and fast query speed. However, there is a defect of insufficiency and …

In recent years, the deep hashing image retrieval algorithm has become a hot spot in current
research. Although the deep hashing algorithm has achieved good results in image …

Hashing is a promising technique to tackle the problem of scalable retrieval, and it generally
consists two major components, namely hash code generation and hash functions learning …

Deep hashing methods utilize an end-to-end framework to mutually learn feature
representations and hash codes, thereby achieving a better retrieval performance …

Deep hashing has been an important research topic for using deep learning to boost
performance of hash learning. Most existing deep supervised hashing methods mainly focus …

Due to the low computational cost of Hamming distance, hashing-based image retrieval has
been universally acknowledged. Therefore, it is becoming increasingly important to quickly …

Deep hashing combines feature extraction or representation with hash coding jointly, which
can significantly improve the speed of large-scale image retrieval. However, we notice that …