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 …
against a query image. Generally, the similarity between the representative features of the …
Deep learning for approximate nearest neighbour search: A survey and future directions
Approximate nearest neighbour search (ANNS) in high-dimensional space is an essential
and fundamental operation in many applications from many domains such as multimedia …
and fundamental operation in many applications from many domains such as multimedia …
A survey on deep hashing methods
Nearest neighbor search aims at obtaining the samples in the database with the smallest
distances from them to the queries, which is a basic task in a range of fields, including …
distances from them to the queries, which is a basic task in a range of fields, including …
Unsupervised deep hashing through learning soft pseudo label for remote sensing image retrieval
Unsupervised hashing is an important approach for large-scale content-based remote
sensing (RS) image retrieval. Existing unsupervised hashing methods usually utilize data …
sensing (RS) image retrieval. Existing unsupervised hashing methods usually utilize data …
Adaptive structural similarity preserving for unsupervised cross modal hashing
Cross-modal hashing is an important approach for multimodal data management and
application. Existing unsupervised cross-modal hashing algorithms mainly rely on data …
application. Existing unsupervised cross-modal hashing algorithms mainly rely on data …
A statistical approach to mining semantic similarity for deep unsupervised hashing
The majority of deep unsupervised hashing methods usually first construct pairwise
semantic similarity information and then learn to map images into compact hash codes while …
semantic similarity information and then learn to map images into compact hash codes while …
Unsupervised hashing retrieval via efficient correlation distillation
Z **, X Wang, P Cheng - … on Circuits and Systems for Video …, 2023 - ieeexplore.ieee.org
Deep hashing has been widely used in multimedia retrieval systems due to its storage and
computation efficiency. Unsupervised hashing has received a lot of attention in recent years …
computation efficiency. Unsupervised hashing has received a lot of attention in recent years …
A two-step cross-modal hashing by exploiting label correlations and preserving similarity in both steps
In this paper, we present a novel Two-stEp Cross-modal Hashing method, TECH for short,
for cross-modal retrieval tasks. As a two-step method, it first learns hash codes based on …
for cross-modal retrieval tasks. As a two-step method, it first learns hash codes based on …
Clustering-driven unsupervised deep hashing for image retrieval
Unsupervised deep hash functions are complicated due to the challenges of learning
discriminative clusters and the absence of similarity-sensitive objectives. Existing …
discriminative clusters and the absence of similarity-sensitive objectives. Existing …
Toward effective domain adaptive retrieval
This paper studies the problem of unsupervised domain adaptive hashing, which is less-
explored but emerging for efficient image retrieval, particularly for cross-domain retrieval …
explored but emerging for efficient image retrieval, particularly for cross-domain retrieval …