Cross-modal hashing has sparked much attention in large-scale information retrieval for its
storage and query efficiency. Despite the great success achieved by supervised …

Hashing could significantly accelerate large-scale image search by transforming the high-
dimensional features into binary Hamming space, where efficient similarity search can be …

Recent years have witnessed the wide application of hashing for large-scale image retrieval,
because of its high computation efficiency and low storage cost. Particularly, benefiting from …

Ideation is a source of innovation and creativity, and is commonly used in early stages of
engineering design processes. This paper proposes an integrated approach for enhancing …

Multi-modal hashing fuses multi-modal features at both offline training and online query
stage for compact binary hash learning. It has aroused extensive attention in research filed …

Unsupervised hashing can desirably support scalable content-based image retrieval for its
appealing advantages of semantic label independence, memory, and search efficiency …

In light of the ability to enable efficient storage and fast query for big data, hashing
techniques for cross-modal search have aroused extensive attention. Despite the great …

While deep neural networks have recently achieved promising results on the image
captioning task, they do not explicitly use the structural visual and textual knowledge within …

Hashing has recently received substantial attention in large-scale multimedia search for its
extremely low-cost storage cost and high retrieval efficiency. However, most existing …

Despite significant progress in supervised hashing, there are three common limitations of
existing methods. First, most pioneer methods discretely learn hash codes bit by bit, making …