Applications of Artificial Intelligence, Machine Learning, Deep Learning, and Explainable AI (XAI)

Dear Colleagues,

Artificial intelligence (AI) with machine learning and deep learning models has been widely applied in numerous domains, including medical imaging, healthcare, industrial manufacturing, sports, and many more. In recent years, many efforts have been made to improve the interpretability of the decisions of machine learning and deep learning algorithms. Explainable Artificial Intelligence (XAI) has been established as a new research area, which aims to provide new methodologies and algorithms to enhance transparency and reliability to both the decisions made by predictive algorithms and the contributions and importance of individual features to the outcome.

The purpose of this Special Issue is to report on the advances in state-of-the-art research on artificial intelligence machine learning, deep learning, and explainable AI applications. The advances in the state-of-the-art for addressing real-world AI applications are of great interest.

The research domains may involve (but are not limited to):

• Medical Image and Signal Processing
• Uncertainty detection, Synthesis, and registration of Images
• Detection from noisy labels and limited data
• Semi-supervised/Self-supervised detection
• Affective Computing
• Computer vision based Intelligent applications
• Intelligent Applications using Augmented and Virtual Reality
• Healthcare Intelligence
• Advanced security using AI
• AI-enabled decision support systems
• Image processing applications
• XAI methods for Deep Learning (e.g., medical domain, industrial applications, security, surveillance)
• Multimodal XAI approaches

Dr. Pratheepan Yogarajah
Dr. Muthu Subash Kavitha
Dr. Lamiaa Abdel-Hamid
Dr. Ananthakrishnan Balasundaram
Guest Editors

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