An overview of cross-media retrieval: Concepts, methodologies, benchmarks, and challenges
Multimedia retrieval plays an indispensable role in big data utilization. Past efforts mainly
focused on single-media retrieval. However, the requirements of users are highly flexible …
focused on single-media retrieval. However, the requirements of users are highly flexible …
A comprehensive survey on cross-modal retrieval
In recent years, cross-modal retrieval has drawn much attention due to the rapid growth of
multimodal data. It takes one type of data as the query to retrieve relevant data of another …
multimodal data. It takes one type of data as the query to retrieve relevant data of another …
MST-GAT: A multimodal spatial–temporal graph attention network for time series anomaly detection
Multimodal time series (MTS) anomaly detection is crucial for maintaining the safety and
stability of working devices (eg, water treatment system and spacecraft), whose data are …
stability of working devices (eg, water treatment system and spacecraft), whose data are …
Deep cross-modal hashing
Due to its low storage cost and fast query speed, cross-modal hashing (CMH) has been
widely used for similarity search in multimedia retrieval applications. However, most existing …
widely used for similarity search in multimedia retrieval applications. However, most existing …
Triplet-based deep hashing network for cross-modal retrieval
Given the benefits of its low storage requirements and high retrieval efficiency, hashing has
recently received increasing attention. In particular, cross-modal hashing has been widely …
recently received increasing attention. In particular, cross-modal hashing has been widely …
Learning discriminative binary codes for large-scale cross-modal retrieval
Hashing based methods have attracted considerable attention for efficient cross-modal
retrieval on large-scale multimedia data. The core problem of cross-modal hashing is how to …
retrieval on large-scale multimedia data. The core problem of cross-modal hashing is how to …
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 …
Semantics-preserving hashing for cross-view retrieval
With benefits of low storage costs and high query speeds, hashing methods are widely
researched for efficiently retrieving large-scale data, which commonly contains multiple …
researched for efficiently retrieving large-scale data, which commonly contains multiple …
Collective matrix factorization hashing for multimodal data
Nearest neighbor search methods based on hashing have attracted considerable attention
for effective and efficient large-scale similarity search in computer vision and information …
for effective and efficient large-scale similarity search in computer vision and information …
Large-scale supervised multimodal hashing with semantic correlation maximization
Due to its low storage cost and fast query speed, hashing has been widely adopted for
similarity search in multimedia data. In particular, more and more attentions have been …
similarity search in multimedia data. In particular, more and more attentions have been …