Textbook in PDF format

This book explores the interdisciplinary nature of Machine Learning in multimedia, highlighting its intersections with fields such as computer vision, natural language processing (NLP), and audio signal processing.
Machine Learning in Multimedia: Unlocking the Power of Visual and Auditory Intelligence serves as a comprehensive guide to navigating this exciting terrain where Artificial Intelligence (AI) meets the rich tapestry of visual and auditory data. At its core, this book seeks to unravel the mysteries and unveil the potential of Machine Learning in the realm of multimedia. Whether it's enhancing user experiences in virtual environments, revolutionizing medical diagnostics, or shaping the future of entertainment, the impact of Machine Learning in multimedia is profound and far-reaching. The journey begins with a thorough exploration of the foundational principles of Machine Learning, providing readers with a solid understanding of algorithms, models, and techniques tailored specifically for multimedia data. Through clear explanations and illustrative examples, readers will gain insights into how Machine Learning algorithms can be trained to extract meaningful patterns and insights from diverse forms of multimedia content. Moving beyond theory, this book delves into practical implementations and real-world applications of Machine Learning in multimedia. Through a series of case studies and examples, readers will witness firsthand how Machine Learning algorithms are transforming industries and reshaping the way we interact with multimedia content. Whether it's improving image recognition accuracy in autonomous vehicles, enabling personalized recommendations in streaming platforms, or enhancing speech recognition systems for better accessibility, the possibilities are limitless.
Whether you’re a seasoned researcher, a curious student, or a practitioner looking to leverage the power of AI, this book is designed to provide you with a deep dive into the intersection of multimedia and Machine Learning. Throughout the chapters, we explore the foundational principles of Machine Learning, delving into algorithms, models, and techniques tailored specifically to multimedia data. From image classification and object detection to speech recognition and audio processing, each topic is meticulously crafted to provide both theoretical insights and practical implementations. Moreover, this book goes beyond mere technical discussions. We delve into real-world case studies and applications, showcasing how Machine Learning is revolutionizing industries and reshaping the way we interact with multimedia content.
This book will be helpful to Computer Science, Data Science, and Artificial Intelligence researchers, students, and professionals looking to unlock the full potential of visual and auditory intelligence through the power of Machine Learning.
Preface
Machine Learning Techniques for Accurate Prediction and Detection of Chronic Diseases
A Novel Approach to Multimedia Malware Detection Using Bi-LSTM and Attention Mechanisms
Exploring Machine Learning Applications for Enhancing Security and Privacy in Multimedia IoT: A Comprehensive Review
Advanced Machine Learning Strategies for Road Object Detection in Multimedia Environments
A Multimedia-Driven Machine Learning Approach to Mastitis Detection in Dairy Cattle
Music Genre Classification Using Long Short-Term Memory (LSTM) Networks: Analyzing Audio Spectrograms for Enhanced Multimedia Understanding
Deep Learning–Based Image Recognition for Autonomous Vehicles: Enhancing Safety and Efficiency
Identification of Heart Disease Risk in Early Ages with Bagging Techniques
EEG-Based Emotion Recognition Using SVM Classifier
Prediction of Neonatal Mortality from Jaundice Using Machine Learning
Implementation of ML Techniques for Heart Prediction in Healthcare
Analyzing the Performance of ML Classification Algorithms for Stroke Prediction