Computational Knowledge Vision: The First Footprints presents a novel, advanced framework which combines structuralized knowledge and visual models. In advanced image and visual perception studies, a visual model's understanding and reasoning ability often determines whether it works well in complex scenarios. This book presents state-of-the-art mainstream vision models for visual perception. As computer vision is one of the key gateways to artificial intelligence and a significant component of modern intelligent systems, this book delves into computer vision systems that are highly specialized and very limited in their ability to do visual reasoning and causal inference. Questions naturally arise in this arena, including (1) How can human knowledge be incorporated with visual models? (2) How does human knowledge promote the performance of visual models? To address these problems, this book proposes a new framework for computer vision–computational knowledge vision. - Presents a concept and basic framework of Computational Knowledge Vision that extends the knowledge engineering methodology to the computer vision field - Discusses neural networks, meta-learning, graphs, and Transformer models - Illustrates a basic framework for Computational Knowledge Vision whose essential techniques include structuralized knowledge, knowledge projection, and conditional feedback
The Intelligent Systems Series comprises titles that present state-of-the-art knowledge and the latest advances in intelligent systems. Its scope includes theoretical studies, design methods, and real-world implementations and applications. Flexible manipulators play a critical role in applications in a diverse range of fields, such as construction automation, environmental applications, and space engineering. Due to the complexity of the link deformation and dynamics, the research effort on accurate modeling and high performance control of flexible manipulators has increased dramatically in recent years. This book presents analysis, data and insights that will of particular use for researchers and engineers working on the optimization and control of robotic manipulators and automation systems. Government and industry groups have specifically stressed the importance of innovation in robotics, manufacturing automation, and control systems for maintaining innovation and high-value-added manufacturing Discusses the latest research on the quantitative effects of size, shape, mass distribution, tip load, on the dynamics and operational performance of flexible manipulators Presents unique analyses critical to the effective modeling and optimization of manipulators: hard to find data unavailable elsewhere
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