Recent developments of content-based image retrieval (CBIR)

X Li, J Yang, J Ma - Neurocomputing, 2021 - Elsevier
With the development of Internet technology and the popularity of digital devices, Content-
Based Image Retrieval (CBIR) has been quickly developed and applied in various fields …

Recent advance in content-based image retrieval: A literature survey

W Zhou, H Li, Q Tian - arxiv preprint arxiv:1706.06064, 2017 - arxiv.org
The explosive increase and ubiquitous accessibility of visual data on the Web have led to
the prosperity of research activity in image search or retrieval. With the ignorance of visual …

Deep supervised hashing for fast image retrieval

H Liu, R Wang, S Shan, X Chen - Proceedings of the IEEE …, 2016 - openaccess.thecvf.com
In this paper, we present a new hashing method to learn compact binary codes for highly
efficient image retrieval on large-scale datasets. While the complex image appearance …

A survey on learning to hash

J Wang, T Zhang, N Sebe… - IEEE transactions on …, 2017 - ieeexplore.ieee.org
Nearest neighbor search is a problem of finding the data points from the database such that
the distances from them to the query point are the smallest. Learning to hash is one of the …

Deep multi-view enhancement hashing for image retrieval

C Yan, B Gong, Y Wei, Y Gao - IEEE Transactions on Pattern …, 2020 - ieeexplore.ieee.org
Hashing is an efficient method for nearest neighbor search in large-scale data space by
embedding high-dimensional feature descriptors into a similarity preserving Hamming …

Hashnet: Deep learning to hash by continuation

Z Cao, M Long, J Wang, PS Yu - Proceedings of the IEEE …, 2017 - openaccess.thecvf.com
Learning to hash has been widely applied to approximate nearest neighbor search for large-
scale multimedia retrieval, due to its computation efficiency and retrieval quality. Deep …

A decade survey of content based image retrieval using deep learning

SR Dubey - IEEE Transactions on Circuits and Systems for …, 2021 - ieeexplore.ieee.org
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 …

Feature learning based deep supervised hashing with pairwise labels

WJ Li, S Wang, WC Kang - arxiv preprint arxiv:1511.03855, 2015 - arxiv.org
Recent years have witnessed wide application of hashing for large-scale image retrieval.
However, most existing hashing methods are based on hand-crafted features which might …

Deep hashing network for efficient similarity retrieval

H Zhu, M Long, J Wang, Y Cao - … of the AAAI conference on Artificial …, 2016 - ojs.aaai.org
Due to the storage and retrieval efficiency, hashing has been widely deployed to
approximate nearest neighbor search for large-scale multimedia retrieval. Supervised …

Deep fuzzy hashing network for efficient image retrieval

H Lu, M Zhang, X Xu, Y Li… - IEEE transactions on fuzzy …, 2020 - ieeexplore.ieee.org
Hashing methods for efficient image retrieval aim at learning hash functions that map similar
images to semantically correlated binary codes in the Hamming space with similarity well …