Computational Intelligence in Machine Learning

The Book contains 17 in total articles that are accepted and published in the Special Issue “Computational Methods and Application in Machine Learning, 2023” of the MDPI Mathematics journal. The articles cover a wide range of topics with respect to the theory and applications of the computational method in machine learning. These keywords include artificial intelligence big data and analysis, machine learning, deep learning, natural language understanding, pattern recognition, computer vision, information retrieval, data mining, bioinformatics and biomedical applications, reinforcement learning, multimedia analysis and retrieval, multimodal representation learning, feature selection, clustering, etc.

Machine learning and computational intelligence are currently among the hottest research directions and have been applied to various areas with many successes, such as fields of image processing, point cloud processing, and natural language processing. Researchers explore many intelligent algorithms which are characterized by computational adaptability, robustness, and high-level performance. These algorithms facilitate intelligent behavior in complex and dynamic environments and the development of technology that enables machines to think, behave, or act more humanely. This book, consisting of 10 articles written by research experts on topics of interest, reports on the latest research in machine learning and computational intelligence. Many novel and interesting methods are introduced, which we hope will provide guiding significance for the further development of machine learning and computational intelligence.

This book comprises the proceedings of the 4th International Conference on Machine Intelligence and Signal Processing (MISP2022). The contents of this book focus on research advancements in machine intelligence, signal processing, and applications. The book covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. It also includes the progress in signal processing to process the normal and abnormal categories of real-world signals such as signals generated from IoT devices, smart systems, speech, videos and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), electromyogram (EMG), etc. This book proves to be a valuable resource for those in academia and industry.

“Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence.”
– Prof. Terrence J. Sejnowski, Computational Neurobiologist