Enhanced Image Retrieval Using Multiscale Deep Feature Fusion in Supervised Hashing
In recent years, deep-network-based hashing has gained prominence in image retrieval for its ability to generate compact and efficient binary representations. However, most existing methods predominantly focus on high-level semantic features extracted from the final layers of networks, often neglect...
Saved in:
Main Authors: | Amina Belalia, Kamel Belloulata, Adil Redaoui |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-01-01
|
Series: | Journal of Imaging |
Subjects: | |
Online Access: | https://www.mdpi.com/2313-433X/11/1/20 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Dual-branch autoencoder network for attacking deep hashing image retrieval models
by: Sizheng FU, et al.
Published: (2023-11-01) -
A ranking hashing algorithm based on listwise supervision
by: Anbang YANG, et al.
Published: (2019-05-01) -
Research and development of hash retrieval technology based on deep learning
by: Mingwen YUAN, et al.
Published: (2018-10-01) -
Trojan message attack on the concatenated hash functions
by: Shi-Wei CHEN, et al.
Published: (2016-08-01) -
Robust image hashing method from global perception features of human visual cortex
by: SUN Rui1, et al.
Published: (2011-01-01)