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Présentation Swarm Intelligence de Format Broché
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Résumé : In this approach it seeks to present both solid and comprehensive theoretical foundations and examples using the main Computational Intelligence libraries, in programming languages such as Python and R. Real world applications have also been provided in areas as diverse as medicine, biology and industrial applications.
Biographie: Wellington Pinheiro dos Santos is an Associate Professor at the Department of Biomedical Engineering at the Federal University of Pernambuco (UFPE), Brazil. He is a DSc in Electrical Engineering at the Federal University of Campina Grande (UFCG, 2009), and a MSc (2003) and BSc (2001) in Electrical and Computer Engineering at UFPE, Brazil. His main research interests are pattern recognition, machine learning, intelligent diagnosis systems, evolutionary computing, applied neuroscience, and artificial intelligence in health. Juliana Carneiro Gomes is a Biomedical Engineer from the Federal University of Pernambuco (UFPE, 2016), with a sandwich period at Mercer University, USA. She worked as a researcher at the Advanced Imaging Algorithms and Instrumentation Laboratory at Johns Hopkins University, USA. She is a Master in Biomedical Engineering (UFPE, 2019) and a PhD student in Computer Engineering at the University of Pernambuco (UPE). She is a Professor at the Physics Department at UFPE. Valter Augusto de Freitas Barbosa has a PhD in Mechanical Engineering (2022), a Master in Biomedical Engineering (2017) and a Biomedical Engineer from the Federal University of Pernambuco (2014), Brazil, with a sandwich period at the Universit? de Technologie de Compi?gne, France. He is currently an Assistant Professor at the Federal Rural University of Pernambuco. His research interests are focused on pattern recognition, artificial intelligence and deep neural networks.
Sommaire: SECTION 1: FUNDAMENTALS AND ADVANCEMENTS ON SWARM INTELLIGENCE 1. Swarm Intelligence Based Algorithm for Feature Selection in High-Dimensional Datasets 2. Swarm Intelligence for Data Mining 3. Leveraging Center-Based Sampling Theory for Enhancing Particle Swarm Classification of Textual Data 4. Reinforcement Learning for Out-of-the-box Parameter Control for Evolutionary and Swarm-based Algorithm SECTION 2: APPLICATIONS 5. Recognition of Emotions in the Elderly Through Audio Signal Analysis 6. Recognition of Emotions in the Elderly through Facial Expressions: A Machine Learning-Based Approach 7. Identification of Emotion Parameters in Music to Modulate Human Affective States 8. Clinical Decision Support in the Care of Symptomatic Patients with COVID-19: An Approach Based on Machine Learning and Swarm Intelligence 9. The Sound of the Mind: Detection of Common Mental Disorders Using Vocal Acoustic Analysis and Machine Learning
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