Data clustering: application and trends
Clustering has primarily been used as an analytical technique to group unlabeled data for
extracting meaningful information. The fact that no clustering algorithm can solve all …
extracting meaningful information. The fact that no clustering algorithm can solve all …
Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook
As cities continue to burgeon, Urban Computing emerges as a pivotal discipline for
sustainable development by harnessing the power of cross-domain data fusion from diverse …
sustainable development by harnessing the power of cross-domain data fusion from diverse …
A novel multimodal fusion framework for early diagnosis and accurate classification of COVID-19 patients using X-ray images and speech signal processing …
Background and objective COVID-19 outbreak has become one of the most challenging
problems for human being. It is a communicable disease caused by a new coronavirus …
problems for human being. It is a communicable disease caused by a new coronavirus …
Research status and evolution trends of emergency information resource management: based on bibliometric analysis from 2003 to 2022
Q Cheng, S Zhang - International journal of disaster risk reduction, 2023 - Elsevier
As big data and artificial intelligence technologies are being increasingly applied in
emergency management activities, effective information resource management has become …
emergency management activities, effective information resource management has become …
CrossFuse: A novel cross attention mechanism based infrared and visible image fusion approach
Multimodal visual information fusion aims to integrate the multi-sensor data into a single
image which contains more complementary information and less redundant features …
image which contains more complementary information and less redundant features …
Cross-directional consistency network with adaptive layer normalization for multi-spectral vehicle re-identification and a high-quality benchmark
To tackle the challenge of vehicle re-identification (Re-ID) in complex lighting environments
and diverse scenes, multi-spectral sources like visible and infrared information are taken …
and diverse scenes, multi-spectral sources like visible and infrared information are taken …
Deep model fusion: A survey
Deep model fusion/merging is an emerging technique that merges the parameters or
predictions of multiple deep learning models into a single one. It combines the abilities of …
predictions of multiple deep learning models into a single one. It combines the abilities of …
Characteristic evaluation via multi-sensor information fusion strategy for spherical underwater robots
Currently, most of the existing fusion methods ignore the rich multi-source information of
different types of sensor nodes in the underwater unknown environment, which makes it …
different types of sensor nodes in the underwater unknown environment, which makes it …
A social media event detection framework based on transformers and swarm optimization for public notification of crises and emergency management
Social media allows the spread of vital information regarding crises and emergencies. Thus,
emergency management systems can benefit from social media because they can be used …
emergency management systems can benefit from social media because they can be used …
Automated multimodal sensemaking: Ontology-based integration of linguistic frames and visual data
Frame evocation from visual data is an essential process for multimodal sensemaking, due
to the multimodal abstraction provided by frame semantics. However, there is a scarcity of …
to the multimodal abstraction provided by frame semantics. However, there is a scarcity of …