Learning to hash for indexing big data—A survey
The explosive growth in Big Data has attracted much attention in designing efficient indexing
and search methods recently. In many critical applications such as large-scale search and …
and search methods recently. In many critical applications such as large-scale search and …
Social fingerprinting: detection of spambot groups through DNA-inspired behavioral modeling
Spambot detection in online social networks is a long-lasting challenge involving the study
and design of detection techniques capable of efficiently identifying ever-evolving …
and design of detection techniques capable of efficiently identifying ever-evolving …
DNA-inspired online behavioral modeling and its application to spambot detection
A novel, simple, and effective approach to modeling online user behavior extracts and
analyzes digital DNA sequences from user online actions and uses Twitter as a benchmark …
analyzes digital DNA sequences from user online actions and uses Twitter as a benchmark …
[PDF][PDF] Deep multimodal hashing with orthogonal regularization
Hashing is an important method for performing efficient similarity search. With the explosive
growth of multimodal data, how to learn hashing-based compact representations for …
growth of multimodal data, how to learn hashing-based compact representations for …
WATCH: Two-stage discrete cross-media hashing
Due to the explosive growth of multimedia data in recent years, cross-media hashing (CMH)
approaches have recently received increasing attention. To learn the hash codes, most …
approaches have recently received increasing attention. To learn the hash codes, most …
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 …
BitHash: An efficient bitwise locality sensitive hashing method with applications
Abstract Locality Sensitive Hashing has been applied to detecting near-duplicate images,
videos and web documents. In this paper we present a Bitwise Locality Sensitive method by …
videos and web documents. In this paper we present a Bitwise Locality Sensitive method by …
Non-transitive hashing with latent similarity components
Approximating the semantic similarity between entities in the learned Hamming space is the
key for supervised hashing techniques. The semantic similarities between entities are often …
key for supervised hashing techniques. The semantic similarities between entities are often …
Sub-selective quantization for learning binary codes in large-scale image search
Recently with the explosive growth of visual content on the Internet, large-scale image
search has attracted intensive attention. It has been shown that mapping high-dimensional …
search has attracted intensive attention. It has been shown that mapping high-dimensional …
A Bayesian Hashing approach and its application to face recognition
With the rapid development in the computer vision community, many recent studies show
that high-dimensional feature representations can produce better accuracies in various …
that high-dimensional feature representations can produce better accuracies in various …