Innovations in Computer Vision and Data Classification

This book explores the dynamic world of data classification, focusing on real-world applications. The book takes you on a journey through the applications of reconfigurable hardware, machine learning, and computer vision in diverse domains. Readers will discover such topics as how Field-Programmable Gate Arrays (FPGAs) expedite pandemic data analysis or how computer vision transforms healthcare through automated skin cancer diagnosis. Special attention is given to environmental data classification, energy-efficient solutions for neural network applications, and real-time performance analysis of energy conversion algorithms. The author guides readers through practical implementations, ensuring a comprehensive understanding of each topic. Whether a researcher, engineer, or student, this book equips readers to make data-driven decisions, optimize systems, and create innovative solutions in fields ranging from healthcare to environmental monitoring. - Explores advancements in data classification, including FPGA acceleration and computer vision-based diagnosis; - Presents data classification with real-world examples from healthcare, environmental science, and energy conversion; - Includes how to apply complex concepts with ease through a didactic approach and hands-on guidance.