Computer Vision and Deep Learning for Visual Understanding

Dear Colleagues,

The Special Issue explores the latest advances in computer vision, deep learning, and visual intelligence that are transforming the analysis, understanding, and interpretation of image and video data. This Special Issue brings together innovative research and technological developments from a wide range of disciplines, emphasizing both theoretical breakthroughs and practical applications in academia, industry, healthcare, and intelligent systems.

Key themes explored in this issue include:

1. Advanced Computer Vision and Deep Learning Algorithms:
   The issue highlights novel methodologies and state-of-the-art architectures for image and video analysis. Topics include object detection, image segmentation, visual tracking, scene understanding, image enhancement, video understanding, and efficient deep learning models designed to improve accuracy, robustness, and computational efficiency.
2. Foundation Models, Generative AI, and Multimodal Learning:
   Recent developments in foundation models, vision transformers, vision-language models, generative AI, and multimodal learning are reshaping visual intelligence. This Special Issue welcomes contributions that leverage these emerging paradigms to address complex challenges in image and video understanding, content generation, visual reasoning, and human-centered AI applications.
3. Healthcare and Medical Imaging Applications:
   Computer vision and deep learning continue to revolutionize healthcare through advanced medical image analysis and computer-aided diagnosis. Contributions are encouraged on medical image segmentation, disease detection, radiological image analysis, digital pathology, healthcare decision support systems, and AI-driven diagnostic tools that enhance clinical outcomes and patient care.
4. Real-Time Processing, Edge AI, and Intelligent Surveillance:
   The growing demand for real-time image and video analytics has accelerated research in efficient and scalable AI systems. The issue explores real-time computer vision solutions for intelligent surveillance, smart monitoring, anomaly detection, edge AI deployment, low-power embedded systems, and latency-sensitive applications in dynamic environments.
5. Autonomous Systems, Robotics, and Smart Transportation:
   Visual perception is a key component of autonomous and intelligent systems. This Special Issue examines advances in computer vision and deep learning for autonomous vehicles, robotics, unmanned aerial systems, intelligent transportation systems, navigation, environmental perception, and decision-making in complex real-world scenarios.
6. Emerging Applications and Future Directions:
   The issue also investigates emerging applications of computer vision and deep learning across diverse sectors, including smart manufacturing, Industry 5.0, remote sensing, precision agriculture, environmental monitoring, multimedia systems, augmented and virtual reality, human-computer interaction, cybersecurity, and IoT-enabled intelligent environments. Particular attention is given to explainable AI, trustworthy AI, privacy-preserving vision systems, and sustainable AI solutions that address future technological and societal challenges.

This Special Issue aims to provide a comprehensive platform for researchers, engineers, and practitioners to share cutting-edge developments and innovative applications that advance the state of the art in computer vision, deep learning, and visual intelligence.

Dr. Abdussalam Elhanashi
Dr. Pierpaolo Dini
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• computer vision
• deep learning
• image analysis
• video analysis
• image processing
• video processing
• visual intelligence
• foundation models
• vision foundation models
• vision-language models
• large vision models
• generative AI
• multimodal learning
• multimodal AI
• explainable AI
• trustworthy AI
• object detection
• object tracking
• scene understanding
• real-time video analytics
• edge AI
• intelligent surveillance
• autonomous systems
• autonomous driving
• robotics vision
• medical image analysis
• healthcare imaging
• smart manufacturing
• remote sensing
• Internet of Things
• intelligent transportation systems