دانلود کتاب تکنیک‌های هوش مصنوعی و یادگیری ماشین در پردازش تصویر و تشخیص اشیا

In the present digital world, the rapid advancement of modern techniques has signif-icantly impacted the wide range of industries from medical imaging and agricul-ture to astronomy and video monitoring. These technological developments have reshaped how we perceive, analyze, and interpret visual data, enhancing automa-tion, accuracy, and efficiency. This book brings together research contributions from experts across various fields to provide a comprehensive exploration of image anal-ysis and object recognition methods. It guides readers through a diverse set of applica-tions, highlighting their transformative role in healthcare, agriculture, security, space exploration, and urban planning. Each chapter addresses a specific topic, offering foundational concepts, technological progress, and real-world applications of image processing techniques.
The book covers the medical imaging applications, where deep learning models have demonstrated exceptional capabilities in automatic organ classification and cardiovascular disease prediction. These advancements in AI-driven diagnostics offer immense potential in assisting medical professionals with precise and effi-cient decision-making. The agriculture domain also benefits significantly from AI and ML integration. With intelligent data-driven approaches, farmers can optimize resources, predict crop yields, and improve sustainability. The fusion of AI with satellite imagery further enhances remote sensing applications, offering unprece-dented insights into ecological monitoring crisis management and land-use anal-ysis. Moving towards object detection, the book examines evolutionary techniques in computer vision, tracing the transition from classical algorithms to state-of-the-art deep learning frameworks. These methodologies are critical in areas such as autonomous vehicles, surveillance systems, and facial recognition.
Moreover, the book extends this exploration to astronomical image processing, where AI techniques have facilitated the identification of celestial bodies and cosmic phenomena, expanding our understanding of the universe. Furthermore, emerging topics such as generative models for image synthesis, disparity estimation in aerial datasets, and human action recognition in video surveillance demonstrate how AI continues to push boundaries in computational vision. The concluding chapters discuss speech processing for stuttering diagnosis and deep learning architectures for biomedical image analysis, showcasing the multidisciplinary applications.
This book aims to serve as a valuable resource for researchers, practitioners, and students keen on exploring the intersection of AI, ML, and image processing. The curated studies provide both theoretical insights and practical implementations, making it a useful guide for academicians and industry professionals alike. As we continue to witness rapid developments in artificial intelligence, we hope this compi-lation inspires future research and innovation, fostering advancements that will shape the next generation of intelligent systems.