AI and Algorithmic Approaches in Cross-Modal Multimedia Analysis and Retrieval for Insights into Well-Being
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms for Multidisciplinary Applications".
Deadline for manuscript submissions: closed (1 November 2023) | Viewed by 643
Special Issue Editors
Interests: big data; multimedia modeling; information retrieval; vision-language matching; computer vision; machine learning and deep learning
Special Issues, Collections and Topics in MDPI journals
Interests: deep learning; computer vision; document analysis; multimodal analysis
Interests: machine learning; healthcare; social sciences
Special Issues, Collections and Topics in MDPI journals
Interests: multimedia forensics; multimedia retrieval; data science; information and communication technology
Interests: multimedia information retrieval; digital memories; mobile device access
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
For decades, the study of human well-being has been a focal point as people aim to understand mental and physical health, social relationships, and connections through both direct and indirect perspectives. The direct perspective involves gathering self-reported data from sources such as wearable sensors, medical profiles, lifelog cameras, and personal social networks to gain insight into individuals' health status, activities, and behaviors. The indirect perspective, on the other hand, captures social data through surrounding sensors, social network interactions, and third-party data to better understand how individuals interact with their environment and society. By leveraging both sources of data, governments, industries, and citizens can make more informed decisions about well-being and its impact areas.
Despite the numerous studies that have been conducted from both perspectives, the use of cross-data multimedia analysis and retrieval to benefit human well-being remains an underrepresented area of research. This Special Issue, in collaboration with the 20th International Conference on Content-based Multimedia Indexing, taking place in France from 20 to 22 September 2023 (https://cbmi2023.org/), aims to bring together experts from various research fields, including the social, life, and natural sciences, to address the latest developments and challenges in cross-data multimedia analysis and retrieval using AI and algorithms to establish a better understanding of well-being. Topics for discussion include food computing, social activity recommendations, anti-infertility, personal training routines, stress reduction methods, mental/physical health improvement, and well-being research, among others, and how these can be advanced through the integration of AI and algorithms in cross-data multimedia analysis and retrieval.
Topics of interest include, but are not limited to:
- Interpretation of multimedia for well-being using AI algorithms;
- Psychological stress and social media use: analysis with AI techniques;
- Health synthetic data generation using machine learning algorithms;
- The effect of media use on well-being: AI-based analysis and recommendations;
- Lifestyle recommendations based on diverse observations using AI-powered algorithms;
- Multimodal personal health lifelong data analysis using AI and big data technologies;
- Multimodal lifelog data analysis and retrieval using AI and machine learning techniques;
- Food in the media and health-conscious consumer: AI-powered analysis and recommendations;
- Training performance indications based on activity lifelogs: AI-powered analysis and predictions;
- The effects of air pollution on human health: AI-based analysis and recommendations;
- Safety driving improvement using multimedia and sensory data analysis using AI and machine learning algorithms.
Dr. Minh-Son Dao
Dr. Vincent Nguyen
Dr. Michael Alexander Riegler
Dr. Duc Tien Dang Nguyen
Dr. Cathal Gurrin
Guest Editors
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