Image Recognition: Progress, Trends and Challenges
This book focuses on research trends in image processing and recognition and corresponding developments. Among them, the book focuses on recent research, especially in the field of advanced human-computer interaction and intelligent computing. Given the existing interaction and recognition of the station, some novel topics are proposed, including how to establish a cognitive model in human-computer interaction and how to express and transfer human knowledge into human-machine image recognition. In an interactive implementation, how to implement user experience through image recognition during machine interaction.
The main contents of this book are arranged as follows. Chapter 1 introduces the research background, research questions, goals, research questions and overviews of this book. Chapter 2 focuses on image calculation methods based on principal component analysis (PCA) and related extensions. Chapter 3 presents an image processing scheme that takes into account the user experience and the optimal balance between QoE and QoS management. Chapter 4 focuses on the performance analysis of methods for classifying image textures based on local binary patterns. Chapter 5 introduces the generation of the anti-network (GAN) and its methods. Chapter 6 mainly discusses the recognition of the interest target as the visual consciousness of the image computing system and proposes a fuzzy target-based interest target differentiation system, which is applied to the extinction enhancement as a display.
Chapter 7 focuses on the implementation and application of PCA image processing and its application in computer vision in the fields of image compression, visual tracking, image recognition, and super-resolution image reconstruction. Chapter 8 introduces various applications of feature extraction and classification techniques in seizures. Chapter 9 introduces some typical image processing based on GAN, involving multiple fields. Chapter 10 introduces an agent-based collaborative information processing framework with stereo vision applications. Chapter 11 introduces the MR application system as a synthesis of the methods and algorithms in each of the above chapters and discusses system design and implementation in terms of functions, modules, and workflows. Chapter 12 evaluates the book, draws conclusions, and proposes advances in image recognition and its advances in image recognition, limitations, and future work, and applies them to intelligent HCI in system design. Objects, human knowledge and user experience, QoE-QoS management, system management, and confidentiality and security.