Computational Knowledge Vision 1st Edition

Grab attention with a fresh perspective on intelligent perception: Computational Knowledge Vision, 1st Edition by Wenbo Zheng and Fei‑Yue Wang offers a rigorous, forward‑looking treatment of how knowledge-driven methods transform computer vision and AI.

Dive into an engaging synthesis of theory and practice that bridges symbolic knowledge representation with modern machine learning. This edition explores core topics—knowledge-based modeling, visual reasoning, pattern recognition, scene understanding, and cognitive vision—through clear exposition and real-world examples that resonate with researchers, engineers, and advanced students. Carefully structured chapters guide readers from foundational concepts to cutting-edge applications in robotics, surveillance, autonomous systems, and intelligent manufacturing.

Why this book matters: it equips you to design vision systems that do more than detect—they interpret, reason, and adapt. Practitioners will find actionable frameworks for integrating domain knowledge into algorithms; academics will appreciate rigorous analysis and research-oriented perspectives; and students will benefit from lucid explanations that build intuition and technical skill.

Globally relevant and technically robust, Computational Knowledge Vision speaks to the international AI community—from Asia’s innovation hubs to Europe and North America’s research labs. Whether you’re developing smarter machines or pursuing advanced study, this book is a foundational resource.

Ready to advance your mastery of knowledge-driven vision? Add Computational Knowledge Vision, 1st Edition by Wenbo Zheng and Fei‑Yue Wang to your collection and start building more intelligent visual systems today.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.