Guest Editors
Dr. Khursheed Aurangzeb, King Saud University, Saudi Arabia
Prof. Yudong Zhang, University of Leicester, UK
Dr. Muhammad Shahid Anwar, Gachon University, South Korea
Dr. Shuihua Wang, University of Leicester, UK.
Summary
The recent progress in the fields of Artificial Intelligence (AI), Machine Learning (ML), data analytics, High-Performance Computing (HPC), and image processing enabled intelligent sensor nodes with decision-making power for different real-life applications such as surveillance, healthcare, smart transportation, smart cities, precision agriculture, etc. The cameras and other sensors are used for surveillance and interaction with the environment in these real-life applications, which generate big data that require the development of sophisticated AI/ML models for interpretation and decision-making.
A healthier lifestyle is of utmost importance for the sustainable progression of modern society. The development of advanced and robust AI/ML models for surveillance and healthcare applications is highly desired due to its direct impact on our lives and lifestyle. There are stringent limitations on the performance of the ML and AI models, which in turn leads to numerous challenges, and opportunities for applying the latest developments in these fields for the betterment of our lifestyles and society.
This special issue welcomes the latest advances and trends related to the development and exploration of advanced AI and machine/deep learning models for signal and image processing applications. It will attract the attention of the research community from around the Globe, addressing genuine issues, emerging applications, and useful solutions for open problems related to the development of AI and machine/deep learning algorithms and techniques for surveillance and other smart cities applications. Therefore, we welcome the submission of original contributions, surveys and review articles including, but not limited to, the following topics:
• Exploration and development of advanced AL, ML, and deep learning models for smart cities, with a focus on surveillance and healthcare application
• Signal and image processing
• Sophisticated machine vision, signal processing, image processing, and evolutionary techniques and algorithms targeting different smart cities applications
• Expanding the domain knowledge for enhancing the training of the machine and deep learning models
• AI Model development for semantic segmentation of biomedical images
• Use cases of vision transformer in Medical, Agriculture and surveillance applications
• Disease detection and diagnosis using advanced machine vision and image processing methods
Keywords
Smart cities, artificial intelligence, data analytics, machine learning, deep learning, electronics systems, surveillance, healthcare, semantic segmentation
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