Multimodal Perception Modeling Based on Advanced Computational Technologies
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: 30 June 2025 | Viewed by 54
Special Issue Editors
Interests: artificial intelligence; machine learning; deep learning; neural networks; activity recognition; wearable computing; computer vision; biometrics; motion health applications
Special Issues, Collections and Topics in MDPI journals
Interests: human activity recognition; speech technology; signal processing; biosignals
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; machine learning; multimedia processing and retrieval; speech technology; affective computing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue aims to explore the advanced computational technologies for modeling human perceptual responses to multimedia stimuli across multiple modalities. With growing interest in areas such as memorability, attention, aesthetics, and persuasion, the use of multimodal approaches is essential for deepening our understanding of how humans interact with multimedia content. By integrating information from visual, textual, auditory, and other sources, as well as gestures and motion, this Issue seeks to advance the field of multimodal modeling, particularly in applications that benefit from a holistic perception of stimuli. Cutting-edge techniques like large multimodal language models (MMLLMs), machine and deep learning, and multi-sensor fusion are expected to play a key role in addressing these challenges.
In addition, motion recognition remains an integral part of this research, as it contributes valuable contextual information to perceptual response modeling. Wearable sensors, smart devices, and computer vision-based methods offer opportunities to analyze motion and gestures. Contributions are invited that examine how motion and activity recognition can enhance the understanding of multimedia experiences, as well as new datasets, algorithms, and architectures that leverage motion data alongside other modalities. Researchers working on intelligent sensing systems, emotion recognition, multimodal fusion, and human–computer interaction are encouraged to submit their work, particularly in healthcare, entertainment, and interactive applications.
Dr. Manuel Gil-Martín
Dr. Rubén San-Segundo
Dr. Fernando Fernández-Martínez
Guest Editors
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Keywords
- multimodal perceptual modeling
- motion recognition
- large multimodal language models (MMLLMs)
- sensor technology
- wearable devices
- computer vision
- multi-sensor fusion
- machine learning
- deep learning
- signal processing
- activity recognition
- multimedia memorability
- attention and aesthetics
- persuasion in multimedia
- olfactory signals
- emotion recognition
- gesture data
- human–computer interaction
- healthcare applications
- biometric systems
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