Deep hashing has been intensively studied and successfully applied in large-scale image
retrieval systems due to its efficiency and effectiveness. Recent studies have recognized that …

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

Online cross-modal hashing has gained attention for its adaptability in processing streaming
data. However, existing methods only define the hard similarity between data using labels …

Deep incremental hashing methods require a large number of original training samples to
preserve old knowledge. However, the old training samples are not always available. This …

Deep incremental hashing has become a subject of considerable interest due to its
capability to learn hash codes in an incremental manner, eliminating the need to generate …

Deep hashing methods have been intensively studied and successfully applied in large-
scale multimedia retrieval. In real-world scenarios, code length can not be set once for all if …

Drone, aka Unmanned aerial vehicle (UAV), has been pervasively applied in geological
hazard monitoring, smart agriculture, and urban planning in the past decade. In this work …

The exponential growth of data raises an unprecedented challenge in data analysis: how to
retrieve interesting information from such large-scale data. Hash learning is a promising …

To solve the problem that the existing ciphertext domain image retrieval system is
challenging to balance security, retrieval efficiency, and retrieval accuracy. This research …

Recent investigations into adversarial deep hashing networks have underscored the
security threat posed by adversarial examples, known as adversarial vulnerability …