Multimodal Cognitive Computing and Deep Representation Learning
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 30 May 2027 | Viewed by 150
Editor
Interests: multimodal cognitive computing: deep representation learning; time series data analysis; 3D point cloud analysis; robust machine learning
Special Issue Information
Dear Colleagues,
Multimodal cognitive computing has emerged as an important paradigm for developing intelligent systems capable of perceiving, understanding, and reasoning over heterogeneous information, including images, text, speech, signals, sensor data, and structured knowledge. Recent progress in deep representation learning, foundation models, and cross-modal reasoning has greatly enhanced the ability of artificial intelligence systems to capture complementary semantic information from complex multimodal environments. However, learning unified, robust, interpretable, and transferable representations remains challenging due to modality heterogeneity, noisy data, limited annotations, domain shifts, privacy concerns, and real-world deployment constraints.
This Special Issue aims to provide a platform for presenting recent advances in multimodal cognitive computing and deep representation learning. Topics of interest include, but are not limited to, multimodal representation learning, cross-modal alignment and retrieval, multimodal fusion, vision-language and audio-visual learning, graph neural networks, transformer-based models, self-supervised and contrastive learning, interpretable and trustworthy AI, federated and privacy-preserving learning, domain adaptation, generalization, and efficient model deployment. We also welcome applications in biomedical analysis, remote sensing, autonomous systems, human-computer interaction, smart healthcare, intelligent manufacturing, and other interdisciplinary fields. Original research articles, reviews, and perspective papers are warmly invited.
Dr. Zheng Wang
Guest Editor
Manuscript Submission Information
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Keywords
- multimodal cognitive computing
- deep representation learning
- multimodal fusion
- cross-modal alignment
- vision-language learning
- self-supervised learning
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