With the advances in deep learning, deep hashing methods have achieved promising
results in recent years. However, tackling the distribution gap between train data and test …

Hashing has attracted attention in recent years due to the rapid growth of image and video
data on the web. Benefiting from recent advances in deep learning, deep supervised …

With the development of technology, the number of data is growing rapidly day by day. How
to perform efficient big data retrieval becomes a critical problem. Similarity-preserving …

Deep hashing methods have received much attention recently, which achieve promising
results by taking advantage of the strong representation power of deep networks. However …

Deep supervised hashing for image retrieval has attracted researchers' attention due to its
high efficiency and superior retrieval performance. Most existing deep supervised hashing …

Abstract In recent years, Convolutional Neural Networks (CNNs) have shown promising
performance on image hashing retrieval. However, due to the information-discarded nature …

Abstract Recently, Convolutional Neural Network (CNN) based hashing method has
achieved its promising performance for image retrieval task. However, tackling the …

Recently, deep supervised hashing methods have shown state-of-the-art performance by
integrating feature learning and hash codes learning into an end-to-end network to generate …

In large-scale image retrieval tasks, hashing methods based on deep convolutional neural
networks (CNNs) play an important role due to elaborate semantic feature representation …

The deep image hashing aims to map the input image into simply binary hash codes via
deep neural networks. Nevertheless, previous deep supervised hashing methods merely …