دانلود کتاب بینایی کامپیوتری کاربردی از طریق هوش مصنوعی -بررسی تأثیر یادگیری ماشین و یادگیری عمیق بر بینایی کامپیوتری

This book unravels the transformative impact of machine learning and deep learning on computer vision, bridging foundational theories with groundbreaking applications. It offers a comprehensive guide for researchers and professionals to navigate the evolving landscape of intelligent visual systems. This book is an exploration of the transformative potential of machine learning and deep learning in computer vision. With chapters authored by experts, it delves into diverse aspects—from foundational theories to groundbreaking applications—providing an in-depth understanding of this dynamic field. The content bridges theoretical insights with real-world applications, offering readers a comprehensive guide to navigating the rapidly evolving landscape of computer vision technologies. It is a valuable resource for students, researchers, and professionals seeking to harness the power of intelligent visual perception systems. The editors, Dr. Jasminder Kaur Sandhu, Dr. Abhishek Kumar, Dr. Rakesh Sahu, and Dr. Sachin Ahuja, present this work as a collaborative effort to inspire innovation and discovery in computer vision, driving the next wave of technological advancements. An Overview of Medical Diagnostics through Artificial Intelligence- Powered Histopathological Imaging and Video Analysis This chapter explores the integration of AI in histopathological imaging, detailing its role in diagnostics. It highlights advancements in video analysis for enhanced precision, emphasizing AI’s potential to revolutionize disease detection and clinical decision-making in modern medical practice. Generative Adversarial Networks: Theory and Application in Synthesis This chapter provides an introduction to GANs, explaining their theoretical foundations and practical applications in data synthesis. It showcases how GANs enable realistic image generation, opening avenues for innovation in various domains like healthcare, gaming, and creative industries. From Pixels to Predictions: Deep Learning for Glaucoma Detection The chapter addresses how deep learning models analyse retinal images for early glaucoma detection. It explores methodologies, datasets, and challenges, underscoring the potential of AI-driven diagnostic tools to enhance ophthalmic care and prevent vision loss globally. Advancements in Computer Vision for Object Detection and Recognition using DenseNet Deep Learning Model This chapter dives into DenseNet’s architecture, detailing its application in object detection and recognition. It examines performance improvements, computational efficiency, and real-world implementations, emphasizing its impact on surveillance, robotics, and intelligent systems. Deep Learning-Based Detection of Cyber Extortion Cyber extortion detection is explored through deep learning algorithms. This chapter discusses identifying threats like ransomware, analyzing attack patterns, and developing robust defenses. It demonstrates the convergence of AI and cybersecurity in safeguarding digital assets. GANs Unleashed: From Theory to Synthetic Realities Delving into GAN advancements, this chapter illustrates their capacity to create synthetic realities. It covers innovative applications in video creation, virtual environments, and artistic endeavors, showcasing the profound impact of synthetic data on technology and creativity. RFID and Computer Vision-Enhanced Automotive Authentication Verification System This chapter presents a hybrid authentication system combining RFID and computer vision for secure vehicular access. It explores implementation strategies, benefits, and applications in smart transportation, enhancing security and user experience. Synergizing Ensemble Learning Techniques for Robust Emotion Detection using EEG Signals This chapter investigates ensemble learning techniques for EEG-based emotion detection. By combining diverse models, it achieves improved accuracy, paving the way for advancements in neurotechnology, healthcare, and human-computer interaction.