Advances and Challenges in Multimodal Pattern Recognition
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 15 March 2026 | Viewed by 4
Special Issue Editors
Interests: multimodal large models; digital humans; embodied intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: information systems; human‒computer interaction; X-reality applications; 3D digitization; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Multimodal pattern recognition has emerged as a crucial area of research, driven by the increasing availability of diverse data modalities such as images, videos, text, speech, and sensory signals. By integrating complementary information from multiple modalities, it is possible to achieve more robust and accurate recognition systems. However, this field also faces significant challenges, including modality alignment, fusion strategies, data sparsity, and scalability issues.
This Special Issue aims to explore cutting-edge advances in multimodal pattern recognition, including topics such as multimodal conditional generation, embodied multimodal intelligence, cross-modal alignment, and the development of large-scale multimodal pretraining models. It also seeks to address challenges such as low-resource learning, real-time applications, and the explainability of multimodal systems. Submissions are encouraged to focus on both foundational research and innovative applications across industries such as healthcare, robotics, autonomous systems, and creative AI. Through this Special Issue, we aim to foster collaboration and inspire breakthroughs in this rapidly evolving field.
Dr. Zhaoxin Fan
Dr. Partarakis Nikolaos
Guest Editors
Manuscript Submission Information
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Keywords
- multimodal conditional generation
- embodied multimodal intelligence
- multimodal alignment and correspondence
- multimodal pretrained models
- cross-modal retrieval and understanding
- multimodal generative AI
- multimodal reinforcement learning
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