The content based image retrieval aims to find the similar images from a large scale dataset
against a query image. Generally, the similarity between the representative features of the …

Autonomous Vehicles (AV) are becoming more capable of navigating in complex
environments with dynamic and changing conditions. A key component that enables these …

In this article, we adopt the maximizing mutual information (MI) approach to tackle the
problem of unsupervised learning of binary hash codes for efficient cross-modal retrieval …

Multi-modal hashing focuses on fusing different modalities and exploring the
complementarity of heterogeneous multi-modal data for compact hash learning. However …

Recent studies show that hashing technology can achieve efficient similarity searching and
many works have been done on supervised deep hash learning. However, under …

In recent years, binary hashing methods have been widely used in large-scale multimedia
retrieval because of the low computational complexity and memory cost. Generally, better …

This paper presents a novel framework, namely Deep Cross-modality Spectral Hashing
(DCSH), to tackle the unsupervised learning problem of binary hash codes for efficient cross …

This article studies deep unsupervised hashing, which has attracted increasing attention in
large-scale image retrieval. The majority of recent approaches usually reconstruct semantic …

The fruit fly Drosophila's olfactory circuit has inspired a new locality sensitive hashing (LSH)
algorithm, FlyHash. In contrast with classical LSH algorithms that produce low dimensional …

Binary hashing is an effective approach for content-based image retrieval, and learning
binary codes with neural networks has attracted increasing attention in recent years …