| Summary: | Computer vision is constantly evolving, and this book has been updated to reflect new topics that have emerged in the field since the first edition⁰́₉s publication. All code used in the book has also been fully updated. This second edition features new material covering image manipulation practices, image segmentation, feature extraction, and object identification using real-life scenarios to help reinforce each concept. These topics are essential for building advanced computer vision applications, and you⁰́₉ll gain a thorough understanding of them. The book⁰́₉s 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, you⁰́₉ll have the knowledge and skills to build your own computer vision applications using neural networks You will: Understand image processing, manipulation techniques, and feature extraction methods Work with convolutional neural networks (CNN), single-shot detector (SSD), and YOLO Utilize large scale model development and cloud infrastructure deployment Gain an overview of FaceNet neural network architecture and develop a facial recognition system
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