learn computer vision using de gollapudi sunila (16 résultats)

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Paperback. Etat : New. Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer vision such as image and object detection, tracking and motion analysis and their applications with examples. The author starts with an introduction to computer vision followed by setting up OpenCV from scratch using Python. The next section discusses specialized image processing and segmentation and how images are stored and processed by a computer. This involves pattern recognition and image tagging using the OpenCV library. Next, you'll work with object detection, video storage and interpretation, and human detection using OpenCV. Tracking and motion is also discussed in detail. The book also discusses creating complex deep learning models with CNN and RNN. The author finally concludes with recent applications and trends in computer vision.After reading this book, you will be able to understand and implement computer vision and its applications with OpenCV using Python. You will also be able to create deep learning models with CNN and RNN and understand how these cutting-edge deep learning architectures work.What You Will LearnUnderstand what computer vision is, and its overall application in intelligent automation systemsDiscover the deep learning techniques required to build computer vision applicationsBuild complex computer vision applications using the latest techniques in OpenCV, Python, and NumPyCreate practical applications and implementations such as face detection and recognition, handwriting recognition, object detection, and tracking and motion analysisWho This Book Is ForThose who have a basic understanding of machine learning and Python and are looking to learn computer vision and its applications.

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Paperback. Etat : Brand New. 151 pages. 9.00x6.25x0.50 inches. In Stock.

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Taschenbuch. Etat : Neu. Neuware -Who This Book Is ForAPress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 172 pp. Englisch.

Taschenbuch. Etat : Neu. Learn Computer Vision Using OpenCV | With Deep Learning CNNs and RNNs | Sunila Gollapudi | Taschenbuch | xx | Englisch | 2019 | APRESS | EAN 9781484242605 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Paperback. Etat : New. Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer vision such as image and object detection, tracking and motion analysis and their applications with examples. The author starts with an introduction to computer vision followed by setting up OpenCV from scratch using Python. The next section discusses specialized image processing and segmentation and how images are stored and processed by a computer. This involves pattern recognition and image tagging using the OpenCV library. Next, you'll work with object detection, video storage and interpretation, and human detection using OpenCV. Tracking and motion is also discussed in detail. The book also discusses creating complex deep learning models with CNN and RNN. The author finally concludes with recent applications and trends in computer vision.After reading this book, you will be able to understand and implement computer vision and its applications with OpenCV using Python. You will also be able to create deep learning models with CNN and RNN and understand how these cutting-edge deep learning architectures work.What You Will LearnUnderstand what computer vision is, and its overall application in intelligent automation systemsDiscover the deep learning techniques required to build computer vision applicationsBuild complex computer vision applications using the latest techniques in OpenCV, Python, and NumPyCreate practical applications and implementations such as face detection and recognition, handwriting recognition, object detection, and tracking and motion analysisWho This Book Is ForThose who have a basic understanding of machine learning and Python and are looking to learn computer vision and its applications.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer vision such as image and object detection, tracking and motion analysis and their applications with examples.The author starts with an introduction to computer vision followed by setting up OpenCV from scratch using Python. The next section discusses specialized image processing and segmentation and how images are stored and processed by a computer. This involves pattern recognition and image tagging using the OpenCV library. Next, you'll work with object detection, video storage and interpretation, and human detection using OpenCV. Tracking and motion is also discussed in detail. The book also discusses creating complex deep learning models with CNN and RNN. The author finally concludes with recent applications and trends in computer vision.After reading this book, you will be able to understand and implement computer vision and its applications with OpenCV using Python. You will also be able to create deep learning models with CNN and RNN and understand how these cutting-edge deep learning architectures work.What You Will LearnUnderstand what computer vision is, and its overall application in intelligent automation systemsDiscover the deep learning techniques required to build computer vision applicationsBuild complex computer vision applications using the latest techniques in OpenCV, Python, and NumPyCreate practical applications and implementations such as face detection and recognition, handwriting recognition, object detection, and tracking and motion analysisWho This Book Is ForThose who have a basic understanding of machine learning and Python and are looking to learn computer vision and its applications. 172 pp. Englisch.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Helps readers get a jump start to computer vision implementationsOffers use-case&nbspdriven implementation for computer vision with focused learning on OpenCV and Python librariesHelps create deep le.

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer vision such as image and object detection, tracking and motion analysis and their applications with examples.The author starts with an introduction to computer vision followed by setting up OpenCV from scratch using Python. The next section discusses specialized image processing and segmentation and how images are stored and processed by a computer. This involves pattern recognition and image tagging using the OpenCV library. Next, you'll work with object detection, video storage and interpretation, and human detection using OpenCV. Tracking and motion is also discussed in detail. The book also discusses creating complex deep learning models with CNN and RNN. The author finally concludes with recent applications and trends in computer vision.After reading this book, you will be able to understand and implement computer vision and its applications with OpenCV using Python. You will also be able to create deep learning models with CNN and RNN and understand how these cutting-edge deep learning architectures work.What You Will LearnUnderstand what computer vision is, and its overall application in intelligent automation systemsDiscover the deep learning techniques required to build computer vision applicationsBuild complex computer vision applications using the latest techniques in OpenCV, Python, and NumPyCreate practical applications and implementations such as face detection and recognition, handwriting recognition, object detection, and tracking and motion analysisWho This Book Is ForThose who have a basic understanding of machine learning and Python and are looking to learn computer vision and its applications.