Convolutional Neural Networks in Visual Computing A Concise Guide
Convolutional Neural Networks in Visual Computing: A Concise Guide by Ragav Venkatesan, published by CRC Press in 2018, offers a focused introduction to the design and deployment of deep learning techniques. This 168-page guide is written in English and aims to provide engineers and students with a foundational understanding of convolutional neural networks (CNNs), emphasizing practical knowledge and theoretical concepts essential for building deep learning systems.
Readers will find that this book serves as a beginner’s toolkit, presenting the core information necessary to grasp and construct CNNs from the ground up. The content is tailored to filter out extraneous material commonly found in other deep learning resources, ensuring a streamlined learning experience. Topics such as machine theory, data science, and software development are woven throughout, making it a relevant resource for those interested in technology and engineering applications.
Official synopsis Publisher
This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner’s guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good theoretical and practical understanding and a complete toolkit of basic information and knowledge required to understand and build convolutional neural networks (CNN) from scratch. The book focuses explicitly on convolutional neural networks, filtering out other material that co-occur in many deep learning books on CNN topics.
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