Submission Deadline: 01 August 2025 View: 744 Submit to Special Issue
Prof. Mohd Amiruddin Abd Rahman
Email: mohdamir@upm.edu.my
Affiliation: Department of Physics, University Putra Malaysia, Kuala Lumpur, 50000, Malaysia
Research Interests: signal processing, pattern recognition/matching/prediction, machine learning algorithms, electromagnetics-related computation and modelling and RF and microwave-based sensor system
Dr. Muhammad Khairul Adib
Email: adib.yusof@upm.edu.my
Affiliation: Muhammad Yusof, Department of Physics, Universiti Putra Malaysia, Kuala Lumpur, 50000, Malaysia
Research Interests: data science, earthquake precursor, ground and space geomagnetic observations
Pattern recognition is crucial in transforming complex data into actionable insights. In recent years as data becomes more abundant and varied, the ability to accurately and efficiently recognize patterns is increasingly important across multiple research domains. Advances in this field have the potential to transform industries by enabling machines to interpret and process information with human-like perception and understanding. This special issue seeks to highlight cutting-edge research and methodologies that push the boundaries of pattern recognition such as such as image and speech recognition, bioinformatics, and artificial intelligence. We aim to provide a platform for researchers and practitioners to share insights, foster collaboration, and inspire future innovation. The scope includes theoretical developments, algorithmic advancements, and practical applications of pattern recognition across diverse fields. The particular topic of interests of this special issue, including but not limited to:
• Novel algorithms and techniques in pattern recognition
• Deep learning and neural networks for pattern analysis
• Real-time pattern recognition systems
• Pattern recognition in big data and data mining
• Applications in computer vision and image processing
• Speech and audio pattern recognition
• Biomedical pattern recognition
• Advances in natural language processing
• Pattern recognition in cybersecurity and fraud detection
• Interdisciplinary approaches to pattern recognition