Multimodal medical data fusion has emerged as a transformative approach in smart
healthcare, enabling a comprehensive understanding of patient health and personalized …

Tire–pavement interaction noise (TPIN) accounts mainly for traffic noise, a sensitive
parameter affecting the eco-based maintenance decision outcome. Consistent methods or …

With the dramatic increase in the amount of multimedia data, cross-modal similarity retrieval
has become one of the most popular yet challenging problems. Hashing offers a promising …

The amount of multi-modal data available on the Internet is enormous. Cross-modal hash
retrieval maps heterogeneous cross-modal data into a single Hamming space to offer fast …

With the increasing popularity of online social networks, more and more people are posting
information, updating their statuses, and searching for topics there. Massive cross-media big …

Most of the image-text retrieval methods carry out accurate results using fine-grained
features for feature alignment. However, extracting the robustness features while …

Cross-modality data translation has attracted great interest in medical image computing.
Deep generative models show performance improvement in addressing related challenges …

Unsupervised cross-modal hashing retrieval across image and text modality is a challenging
task because of the suboptimality of similarity guidance, ie, the joint similarity matrix …

Hashing methods have sparked a great revolution in cross-modal retrieval due to the low
cost of storage and computation. Benefiting from the sufficient semantic information of …

Locality-sensitive hashing (LSH) has gained ever-increasing popularity in similarity search
for large-scale data. It has competitive search performance when the number of generated …