The hashing method is widely used for large-scale image retrieval due to its low time and
space complexity. However, the existing deep hashing methods are mainly designed for …

Hashing algorithm has been widely used to speed up image retrieval due to its compact
binary code and fast distance calculation. The combination with deep learning boosts the …

Hashing methods have been widely used for efficient similarity retrieval on large scale
image database. Traditional hashing methods learn hash functions to generate binary codes …

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 …

Hashing has received a lot of attention in large-scale image retrieval due to its high retrieval
accuracy and speed. Unsupervised deep hashing methods with pseudo-labels suffer from …

Hashing methods have proven to be effective in the field of large-scale image retrieval. In
recent years, the performance of hashing algorithms based on deep learning has greatly …

Hashing methods play an important role in large scale image retrieval. Traditional hashing
methods use hand-crafted features to learn hash functions, which can not capture the high …

Recent years have witnessed wide application of hashing for large-scale image retrieval.
However, most existing hashing methods are based on hand-crafted features which might …

Due to the advantages of retrieval speed and storage space, deep hashing methods have
become a research hotspot in the field of large-scale image retrieval. Most of existing deep …

Hashing has been widely used to approximate the nearest neighbor search for image
retrieval due to its high computation efficiency and low storage requirement. With the …