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 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, im...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berkeley, CA
Apress
[2023]
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| Ausgabe: | Second edition |
| Schlagworte: | |
| Zusammenfassung: | 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 Learn- 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 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 |
| Beschreibung: | xxii, 526 Seiten Illustrationen 1031 gr |
| ISBN: | 9781484298657 |
Internformat
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| 520 | |a 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 Learn- 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 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 | ||
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Datensatz im Suchindex
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| spelling | Ansari, Shamshad Verfasser (DE-588)1215855621 aut Building computer vision applications using artificial neural networks with examples in OpenCV and TensorFlow with Python Shamshad Ansari Second edition Berkeley, CA Apress [2023] xxii, 526 Seiten Illustrationen 1031 gr txt rdacontent n rdamedia nc rdacarrier 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 Learn- 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 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 bicssc bisacsh Python (Computer program language) Open source software Machine learning Hardcover, Softcover / Informatik, EDV/Informatik Erscheint auch als Online-Ausgabe 978-1-4842-9866-4 |
| spellingShingle | Ansari, Shamshad Building computer vision applications using artificial neural networks with examples in OpenCV and TensorFlow with Python bicssc bisacsh Python (Computer program language) Open source software Machine learning |
| title | Building computer vision applications using artificial neural networks with examples in OpenCV and TensorFlow with Python |
| title_auth | Building computer vision applications using artificial neural networks with examples in OpenCV and TensorFlow with Python |
| title_exact_search | Building computer vision applications using artificial neural networks with examples in OpenCV and TensorFlow with Python |
| title_exact_search_txtP | Building computer vision applications using artificial neural networks with examples in OpenCV and TensorFlow with Python |
| title_full | Building computer vision applications using artificial neural networks with examples in OpenCV and TensorFlow with Python Shamshad Ansari |
| title_fullStr | Building computer vision applications using artificial neural networks with examples in OpenCV and TensorFlow with Python Shamshad Ansari |
| title_full_unstemmed | Building computer vision applications using artificial neural networks with examples in OpenCV and TensorFlow with Python Shamshad Ansari |
| title_short | Building computer vision applications using artificial neural networks |
| title_sort | building computer vision applications using artificial neural networks with examples in opencv and tensorflow with python |
| title_sub | with examples in OpenCV and TensorFlow with Python |
| topic | bicssc bisacsh Python (Computer program language) Open source software Machine learning |
| topic_facet | bicssc bisacsh Python (Computer program language) Open source software Machine learning |
| work_keys_str_mv | AT ansarishamshad buildingcomputervisionapplicationsusingartificialneuralnetworkswithexamplesinopencvandtensorflowwithpython |