Shamshad Ansari
Building Computer Vision Applications Using Artificial Neural Networks: With Examples in OpenCV and TensorFlow with Python
Building Computer Vision Applications Using Artificial Neural Networks: With Examples in OpenCV and TensorFlow with Python
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- More about Building Computer Vision Applications Using Artificial Neural Networks: With Examples in OpenCV and TensorFlow with Python
Computer vision is constantly evolving, and this book has been updated to reflect new topics such as image manipulation, segmentation, feature extraction, and object identification. It includes step-by-step examples using OpenCV and TensorFlow with Python and covers large-scale model development and cloud infrastructure deployment. It is for data scientists, deep learning experts, and students with a solid understanding of Python programming.
Format: Paperback / softback
Length: 527 pages
Publication date: 28 November 2023
Publisher: APress
Computer vision is a rapidly advancing field, and this book has been thoroughly revised to incorporate new topics that have emerged since its first edition. All the code used in the book has been updated to ensure its accuracy and relevance.
The second edition of this book includes extensive coverage of image manipulation techniques, image segmentation, feature extraction, and object identification using real-life scenarios. These topics are crucial for developing advanced computer vision applications, and the book provides a comprehensive understanding of them. The source code has been updated from TensorFlow 1.x to 2.x, and includes step-by-step examples using both OpenCV and TensorFlow with Python.
Upon completing this book, readers will have the knowledge and skills to build their own computer vision applications using neural networks. They will understand image processing, manipulation techniques, and feature extraction methods, work with convolutional neural networks (CNNs), single-shot detectors (SSDs), and YOLO, utilize large-scale model development and cloud infrastructure deployment, and gain an overview of FaceNet neural network architecture and develop a facial recognition system.
This book is designed for individuals with a solid understanding of Python programming and a desire to delve into computer vision and machine learning. It will be particularly beneficial to data scientists, deep learning experts, and students.
Weight: 1020g
Dimension: 252 x 177 x 33 (mm)
ISBN-13: 9781484298657
Edition number: 2nd ed.
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