Applied Computer Vision through Artificial Intelligence

Jasminder Kaur Sandhu, Abhishek Kumar, Rakesh Sahu, Sachin Ahuja

• Publisher: Wiley-Scrivener
• Year: 2025
• Print ISBN: 9781394272594
• eBook ISBN: 9781394272617
• Edition: 1
• Topic: Computer Science
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Computer Science

Master the cutting-edge field of computer vision and artificial intelligence with this accessible guide to the applications of machine learning and deep learning for real-world solutions in robotics, healthcare, and autonomous systems.

Applied Computer Vision through Artificial Intelligence provides a thorough and accessible exploration of how machine learning and deep learning are driving breakthroughs in computer vision. This book brings together contributions from leading experts to present state-of-the-art techniques, tools, and frameworks, while demonstrating this technology's applications in healthcare, autonomous systems, surveillance, robotics, and other real-world domains. By blending theory with hands-on insights, this volume equips readers with the knowledge needed to understand, design, and implement AI-powered vision solutions.

Structured to serve both academic and professional audiences, the book not only covers cutting-edge algorithms and methodologies but also addresses pressing challenges, ethical considerations, and future research directions. It serves as a comprehensive reference for researchers, engineers, practitioners, and graduate students, making it an indispensable resource for anyone looking to apply artificial intelligence to solve complex computer vision problems in today's data-driven world.

Table of contents

• Cover
• Series Page
• Title Page
• Copyright Page
• Contents
• Preface
• Chapter 1 An Overview of Medical Diagnostics through Artificial Intelligence-Powered Histopathological Imaging and Video Analysis
• Chapter 2 Generative Adversarial Networks: Theory and Application in Synthesis
• Chapter 3 From Pixels to Predictions: Deep Learning for Glaucoma Detection
• Chapter 4 Advancements in Computer Vision for Object Detection and Recognition using DenseNet Deep Learning Model
• Chapter 5 Deep Learning-Based Detection of Cyber Extortion
• Chapter 6 GANs Unleashed: From Theory to Synthetic Realities
• Chapter 7 RFID and Computer Vision-Enhanced Automotive Authentication Verification System
• Chapter 8 Synergizing Ensemble Learning Techniques for Robust Emotion Detection using EEG Signals
• Chapter 9 Understanding the Unseen: Explainability in Deep Learning for Computer Vision
• Chapter 10 Prefatory Study on Landslide Susceptibility Modeling Based on Binary Random Forest Classifier
• Chapter 11 Improving Digital Interactions using Augmented Reality and Computer Vision
• Chapter 12 The Evolutionary Dynamics of Machine Learning and Deep Learning Architectures in Computer Vision
• Chapter 13 Real-World Applications: Transforming Industries with Computer Vision
• Chapter 14 Revolutionizing Vision Perception with Multimodal Fusion Technologies
• Chapter 15 Object Detection and Localization: Identifying and Pinpointing With Precision
• Chapter 16 Uncertainty Estimation in Deep Learning Based Computer Vision
• Chapter 17 Overcoming Occlusions in Visual Data using Long Short-Term Memory Networks (LSTMs)
• Chapter 18 Transformative Role of Machine Learning and Deep Learning Architecture in Computer Vision
• Chapter 19 A Comprehensive Analysis of Deep Learning and Machine Learning for Semantic Segmentation, and Object Detection in Machine and Robotic Vision
• Chapter 20 From Theoretical Foundations to Data Synthesis: Advanced Applications of Generative Adversarial Networks (GANs)
• Chapter 21 Optimization Techniques in Training Deep Neural Networks for Vision
• About the Editors
• Index
• Also of Interest
• EULA