9781484298657 - Building Computer Vision Applications Using Artificial Neural Networks: With Examples in Opencv and Tensorflow With Python di Ansari, Shamshad (32 risultati)

Paperback. Condizione: Very Good. Second. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

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Paperback or Softback. Condizione: New. Building Computer Vision Applications Using Artificial Neural Networks: With Examples in Opencv and Tensorflow with Python. Book.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: new. Paperback. Computer vision is constantly evolving, and this book has been updated to reflect new topics that have emerged in the field since the first editions 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 youll gain a thorough understanding of them. The books 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, youll have the knowledge and skills to build your own computer vision applications using neural networks What You Will LearnUnderstand image processing, manipulation techniques, and feature extractionmethodsWork with convolutional neural networks (CNN), single-shot detector (SSD), and YOLOUtilize large scale model development and cloud infrastructure deploymentGain an overview of FaceNet neural network architecture and develop a facial recognition systemWho This Book Is ForThose who possess a solid understanding of Python programming and wish to gain an understanding of computer vision and machine learning. It will prove beneficial to data scientists, deep learning experts, and students. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New. 2023. 2nd Edition. paperback. . . . . .

Paperback. Condizione: New. Second Edition. Computer vision is constantly evolving, and this book has been updated to reflect new topics that have emerged in the field since the first edition's 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 you'll gain a thorough understanding of them. The book's 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, you'll have the knowledge and skills to build your own computer vision applications using neural networks What You Will LearnUnderstand image processing, manipulation techniques, and feature extractionmethodsWork with convolutional neural networks (CNN), single-shot detector (SSD), and YOLOUtilize large scale model development and cloud infrastructure deploymentGain an overview of FaceNet neural network architecture and develop a facial recognition systemWho This Book Is ForThose who possess a solid understanding of Python programming and wish to gain an understanding of computer vision and machine learning. It will prove beneficial to data scientists, deep learning experts, and students.

Condizione: New. In.

Condizione: New. 2023. 2nd Edition. paperback. . . . . . Books ship from the US and Ireland.

Paperback. Condizione: Brand New. 2nd edition. 548 pages. 10.01x7.01x1.11 inches. In Stock.

Condizione: New. pp. 548.

Kartoniert / Broschiert. Condizione: New. Computer vision is constantly evolving, and this book has been updated to reflect new topics that have emerged in the field since the first edition s publication. All code used in the book has also been fully updated.This second edition features n.

Condizione: NEW.

Taschenbuch. Condizione: Neu. Building Computer Vision Applications Using Artificial Neural Networks | With Examples in OpenCV and TensorFlow with Python | Shamshad Ansari | Taschenbuch | xxii | Englisch | 2024 | Apress | EAN 9781484298657 | 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. Condizione: new. Paperback. Computer vision is constantly evolving, and this book has been updated to reflect new topics that have emerged in the field since the first editions 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 youll gain a thorough understanding of them. The books 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, youll have the knowledge and skills to build your own computer vision applications using neural networks What You Will LearnUnderstand image processing, manipulation techniques, and feature extractionmethodsWork with convolutional neural networks (CNN), single-shot detector (SSD), and YOLOUtilize large scale model development and cloud infrastructure deploymentGain an overview of FaceNet neural network architecture and develop a facial recognition systemWho This Book Is ForThose who possess a solid understanding of Python programming and wish to gain an understanding of computer vision and machine learning. It will prove beneficial to data scientists, deep learning experts, and students. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Condizione: Gut. Zustand: Gut | Seiten: 548 | Sprache: Englisch | Produktart: Bücher | Computer vision is constantly evolving, and this book has been updated to reflect new topics that have emerged in the field since the first edition¿s 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 yoüll gain a thorough understanding of them. The book¿s 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, yoüll have the knowledge and skills to build your own computer vision applications using neural networks What You Will LearnUnderstand image processing, manipulation techniques, and feature extractionmethodsWork with convolutional neural networks (CNN), single-shot detector (SSD), and YOLOUtilize large scale model development and cloud infrastructure deploymentGain an overview of FaceNet neural network architecture and develop a facial recognition systemWho This Book Is ForThose who possess a solid understanding of Python programming and wish to gain an understanding of computer vision and machine learning. It will prove beneficial to data scientists, deep learning experts, and students.

Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 548 | Sprache: Englisch | Produktart: Bücher | Computer vision is constantly evolving, and this book has been updated to reflect new topics that have emerged in the field since the first edition¿s 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 yoüll gain a thorough understanding of them. The book¿s 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, yoüll have the knowledge and skills to build your own computer vision applications using neural networks What You Will LearnUnderstand image processing, manipulation techniques, and feature extractionmethodsWork with convolutional neural networks (CNN), single-shot detector (SSD), and YOLOUtilize large scale model development and cloud infrastructure deploymentGain an overview of FaceNet neural network architecture and develop a facial recognition systemWho This Book Is ForThose who possess a solid understanding of Python programming and wish to gain an understanding of computer vision and machine learning. It will prove beneficial to data scientists, deep learning experts, and students.

Condizione: Hervorragend. Zustand: Hervorragend | Seiten: 548 | Sprache: Englisch | Produktart: Bücher | Computer vision is constantly evolving, and this book has been updated to reflect new topics that have emerged in the field since the first edition¿s 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 yoüll gain a thorough understanding of them. The book¿s 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, yoüll have the knowledge and skills to build your own computer vision applications using neural networks What You Will LearnUnderstand image processing, manipulation techniques, and feature extractionmethodsWork with convolutional neural networks (CNN), single-shot detector (SSD), and YOLOUtilize large scale model development and cloud infrastructure deploymentGain an overview of FaceNet neural network architecture and develop a facial recognition systemWho This Book Is ForThose who possess a solid understanding of Python programming and wish to gain an understanding of computer vision and machine learning. It will prove beneficial to data scientists, deep learning experts, and students.

Paperback. Condizione: New. Second Edition. Computer vision is constantly evolving, and this book has been updated to reflect new topics that have emerged in the field since the first edition's 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 you'll gain a thorough understanding of them. The book's 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, you'll have the knowledge and skills to build your own computer vision applications using neural networks What You Will LearnUnderstand image processing, manipulation techniques, and feature extractionmethodsWork with convolutional neural networks (CNN), single-shot detector (SSD), and YOLOUtilize large scale model development and cloud infrastructure deploymentGain an overview of FaceNet neural network architecture and develop a facial recognition systemWho This Book Is ForThose who possess a solid understanding of Python programming and wish to gain an understanding of computer vision and machine learning. It will prove beneficial to data scientists, deep learning experts, and students.

Softcover. Condizione: gut. 2023. Building Computer Vision Applications Using Artificial Neural Networks In deutscher Sprache. pages.

Paperback. Condizione: Brand New. 2nd edition. 548 pages. 10.01x7.01x1.11 inches. In Stock. This item is printed on demand.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Computer vision is constantly evolving, and this book has been updated to reflect new topics that have emerged in the field since the first edition's 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 you'll gain a thorough understanding of them. The book's 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, you'll have the knowledge and skills to build your own computer vision applications using neural networksWhat You Will LearnUnderstand image processing, manipulation techniques, and feature extraction methodsWork with convolutional neural networks (CNN), single-shot detector (SSD), and YOLOUtilize large scale model development and cloud infrastructure deploymentGain an overview of FaceNet neural network architecture and develop a facial recognition systemWho This Book Is ForThose who possess a solid understanding of Python programming and wish to gain an understanding of computer vision and machine learning. It will prove beneficial to data scientists, deep learning experts, and students. 548 pp. Englisch.

Condizione: New. PRINT ON DEMAND pp. 548.