Deep Learning for Multimedia Processing Applications

Volume One: Image Security and Intelligent Systems for Multimedia Processing

Uzair Aslam Bhatti, Huang Mengxing, Jingbing Li, Sibghat Ullah Bazai, Muhammad Aamir, Uzair Aslam Bhatti, Huang Mengxing, Jingbing Li, Sibghat Ullah Bazai, Muhammad Aamir

• Publisher: CRC Press
• Year: 2024
• Print ISBN: 9781032548241
• eBook ISBN: 9781003827962
• Edition: 1
• Topic: Computer Science
• Subtopic: Computer Science General
• Index: Computer Science

Deep Learning for Multimedia Processing Applications is a comprehensive guide that explores the revolutionary impact of deep learning techniques in the field of multimedia processing. Written for a wide range of readers, from students to professionals, this book offers a concise and accessible overview of the application of deep learning in various multimedia domains, including image processing, video analysis, audio recognition, and natural language processing.

Divided into two volumes, Volume One begins by introducing the fundamental concepts of deep learning, providing readers with a solid foundation to understand its relevance in multimedia processing. Readers will discover how deep learning techniques enable accurate and efficient image recognition, object detection, semantic segmentation, and image synthesis. The book also covers video analysis techniques, including action recognition, video captioning, and video generation, highlighting the role of deep learning in extracting meaningful information from videos.

Furthermore, the book explores audio processing tasks such as speech recognition, music classification, and sound event detection using deep learning models. It demonstrates how deep learning algorithms can effectively process audio data, opening up new possibilities in multimedia applications. Lastly, the book explores the integration of deep learning with natural language processing techniques, enabling systems to understand, generate, and interpret textual information in multimedia contexts.

Throughout the book, practical examples, code snippets, and real-world case studies are provided to help readers gain hands-on experience in implementing deep learning solutions for multimedia processing. Deep Learning for Multimedia Processing Applications is an essential resource for anyone interested in harnessing the power of deep learning to unlock the vast potential of multimedia data.

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Contents
• Contributors
• Chapter 1 A Novel Robust Watermarking Algorithm for Encrypted Medical Images Based on Non-Subsampled Shearlet Transform and Schur Decomposition
• Chapter 2 Robust Zero Watermarking Algorithm for Encrypted Medical Images Based on SUSAN-DCT
• Chapter 3 Robust Zero Watermarking Algorithm for Encrypted Medical Volume Data Based on PJFM and 3D-DCT
• Chapter 4 Robust Zero Watermarking Algorithm for Medical Images Based on BRISK and DCT
• Chapter 5 Robust Color Images Zero-Watermarking Algorithm Based on Stationary Wavelet Transform and Daisy Descriptor
• Chapter 6 Robust Multi-watermarking Algorithm Based on DarkNet53
• Chapter 7 Robust Multi-watermark Algorithm for Medical Images Based on SqueezeNet Transfer Learning
• Chapter 8 Deep Learning Applications in Digital Image Security: Latest Methods and Techniques
• Chapter 9 Image Fusion Techniques and Applications for Remote Sensing and Medical Images
• Chapter 10Detecting Phishing URLs through Deep Learning Models
• Chapter 11 Augmenting Multimedia Analysis: A Fusion of Deep Learning with Differential Privacy
• Chapter 12 Multi-classification Deep Learning Models for Detecting Multiple Chest Infection Using Cough and Breath Sounds
• Chapter 13 Classifying Traffic Signs Using Convolutional Neural Networks Based on Deep Learning Models
• Chapter 14 Cloud-Based Intrusion Detection System Using a Deep Neural Network and Human-in-the-Loop Decision Making
• Index