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 multi-view enhancement hashing for image retrieval
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 …
embedding high-dimensional feature descriptors into a similarity preserving Hamming …
Distillhash: Unsupervised deep hashing by distilling data pairs
Due to storage and search efficiency, hashing has become significantly prevalent for nearest
neighbor search. Particularly, deep hashing methods have greatly improved the search …
neighbor search. Particularly, deep hashing methods have greatly improved the search …
Deep unsupervised image hashing by maximizing bit entropy
Y Li, J van Gemert - Proceedings of the AAAI Conference on Artificial …, 2021 - ojs.aaai.org
Unsupervised hashing is important for indexing huge image or video collections without
having expensive annotations available. Hashing aims to learn short binary codes for …
having expensive annotations available. Hashing aims to learn short binary codes for …
Deep hashing for secure multimodal biometrics
V Talreja, MC Valenti… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
When compared to unimodal systems, multimodal biometric systems have several
advantages, including lower error rate, higher accuracy, and larger population coverage …
advantages, including lower error rate, higher accuracy, and larger population coverage …
Targeted attack for deep hashing based retrieval
The deep hashing based retrieval method is widely adopted in large-scale image and video
retrieval. However, there is little investigation on its security. In this paper, we propose a …
retrieval. However, there is little investigation on its security. In this paper, we propose a …
SCRATCH: A scalable discrete matrix factorization hashing framework for cross-modal retrieval
In this paper, we present a novel supervised cross-modal hashing framework, namely
Scalable disCRete mATrix faCtorization Hashing (SCRATCH). First, it utilizes collective …
Scalable disCRete mATrix faCtorization Hashing (SCRATCH). First, it utilizes collective …
Graph convolutional multi-modal hashing for flexible multimedia retrieval
Multi-modal hashing makes an important contribution to multimedia retrieval, where a key
challenge is to encode heterogeneous modalities into compact hash codes. To solve this …
challenge is to encode heterogeneous modalities into compact hash codes. To solve this …
Self-supervised video hashing via bidirectional transformers
Most existing unsupervised video hashing methods are built on unidirectional models with
less reliable training objectives, which underuse the correlations among frames and the …
less reliable training objectives, which underuse the correlations among frames and the …
Adaptive partial multi-view hashing for efficient social image retrieval
Social networks allow users to actively upload images and descriptive tags, which has led to
an explosive growth in the number of social images. Multi-view hashing is an efficient …
an explosive growth in the number of social images. Multi-view hashing is an efficient …