Deep Learning Powered Image Animation
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Deep Learning-Powered Image Animation
"Deep Learning-Powered Image Animation" is an illuminating exploration of the fascinating world of image animation and its integration with cutting-edge deep learning techniques. Authored by Harry Jazz, a renowned expert in the field, this book serves as a comprehensive guide for both beginners and experienced practitioners seeking to unlock the potential of deep learning in the realm of image animation. With the explosive growth of deep learning algorithms and advancements in computer vision, the art of image animation has reached unprecedented levels of realism and creativity. In this book, Harry Jazz presents a step-by-step journey, starting from the fundamentals of deep learning, and gradually building up to sophisticated image animation techniques. The book begins with a concise overview of deep learning, providing readers with a solid foundation in neural networks, convolutional neural networks (CNNs), and generative adversarial networks (GANs). Harry Jazz goes on to discuss various methods for data preparation and augmentation, essential for training accurate and robust models for image animation. One of the highlights of the book is the in-depth exploration of key deep learning architectures used in image animation. From the classic VGGNet and ResNet to more recent advancements like U-Net and Pix2Pix, the author offers practical insights into their inner workings, strengths, and limitations. Furthermore, Harry Jazz delves into advanced topics such as facial expression transfer, pose estimation, and style transfer, providing readers with the necessary tools to create dynamic and lifelike animations. The author also addresses the challenges and ethical considerations associated with deep learning-based image animation, emphasizing the importance of responsible and inclusive practices. Packed with numerous code examples, visual illustrations, and real-world applications, "Deep Learning-Powered Image Animation" equips readers with the knowledge and skills to leverage the power of deep learning in creating captivating and realistic image animations. Whether you are an AI enthusiast, a researcher, or a practitioner in the field of computer vision, this book will serve as an invaluable resource to propel your image animation endeavors to new heights.
Deep Learning-Powered Technologies
Author: Khaled Salah Mohamed
language: en
Publisher: Springer Nature
Release Date: 2023-06-23
This book covers various, leading-edge deep learning technologies. The author discusses new applications of deep learning and gives insight into the integration of deep learning with various application domains, such as autonomous driving, augmented reality, AIOT, 5G and beyond.
Machine Learning, Animated
The release of ChatGPT has kicked off an arms race in Machine Learning (ML), however ML has also been described as a black box and very hard to understand. Machine Learning, Animated eases you into basic ML concepts and summarizes the learning process in three words: initialize, adjust and repeat. This is illustrated step by step with animation to show how machines learn: from initial parameter values to adjusting each step, to the final converged parameters and predictions. This book teaches readers to create their own neural networks with dense and convolutional layers, and use them to make binary and multi-category classifications. Readers will learn how to build deep learning game strategies and combine this with reinforcement learning, witnessing AI achieve super-human performance in Atari games such as Breakout, Space Invaders, Seaquest and Beam Rider. Written in a clear and concise style, illustrated with animations and images, this book is particularly appealing to readers with no background in computer science, mathematics or statistics. Access the book's repository at: https://github.com/markhliu/MLA