Learn computer vision using OpenCV: with deep learning CNNs and RNNs
Chapter 1: Artificial Intelligence and Computer Vision -- Chapter 2: OpenCV with Python -- Chapter 3: Deep learning for Computer Vision -- Chapter 4: Image Manipulation and Segmentation -- Chapter 5 : Object Detection and Recognition -- Chapter 6: Motion Analysis and Tracking
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
[Berkeley, CA]
Apress
[2019]
|
| Schlagworte: | |
| Zusammenfassung: | Chapter 1: Artificial Intelligence and Computer Vision -- Chapter 2: OpenCV with Python -- Chapter 3: Deep learning for Computer Vision -- Chapter 4: Image Manipulation and Segmentation -- Chapter 5 : Object Detection and Recognition -- Chapter 6: Motion Analysis and Tracking 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. You will: Understand what computer vision is, and its overall application in intelligent automation systems Discover the deep learning techniques required to build computer vision applications Build complex computer vision applications using the latest techniques in OpenCV, Python, and NumPy Create practical applications and implementations such as face detection and recognition, handwriting recognition, object detection, and tracking and motion analysis |
| Beschreibung: | xx, 151 Seiten Illustrationen |
| ISBN: | 9781484242605 |
Internformat
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| 520 | 3 | |a 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. You will: Understand what computer vision is, and its overall application in intelligent automation systems Discover the deep learning techniques required to build computer vision applications Build complex computer vision applications using the latest techniques in OpenCV, Python, and NumPy Create practical applications and implementations such as face detection and recognition, handwriting recognition, object detection, and tracking and motion analysis | |
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| isbn | 9781484242605 |
| language | English |
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| spelling | Gollapudi, Sunila Verfasser (DE-588)1097414108 aut Learn computer vision using OpenCV with deep learning CNNs and RNNs Sunila Gollapudi [Berkeley, CA] Apress [2019] xx, 151 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier Chapter 1: Artificial Intelligence and Computer Vision -- Chapter 2: OpenCV with Python -- Chapter 3: Deep learning for Computer Vision -- Chapter 4: Image Manipulation and Segmentation -- Chapter 5 : Object Detection and Recognition -- Chapter 6: Motion Analysis and Tracking 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. You will: Understand what computer vision is, and its overall application in intelligent automation systems Discover the deep learning techniques required to build computer vision applications Build complex computer vision applications using the latest techniques in OpenCV, Python, and NumPy Create practical applications and implementations such as face detection and recognition, handwriting recognition, object detection, and tracking and motion analysis OpenCV (DE-588)1038770092 gnd rswk-swf Python Programmiersprache (DE-588)4434275-5 gnd rswk-swf Maschinelles Sehen (DE-588)4129594-8 gnd rswk-swf Deep learning (DE-588)1135597375 gnd rswk-swf Artificial intelligence Python (Computer program language) Open source software Computer programming Artificial Intelligence Maschinelles Sehen (DE-588)4129594-8 s OpenCV (DE-588)1038770092 s Deep learning (DE-588)1135597375 s Python Programmiersprache (DE-588)4434275-5 s 1\p DE-604 Erscheint auch als Online-Ausgabe 978-1-4842-4261-2 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Gollapudi, Sunila Learn computer vision using OpenCV with deep learning CNNs and RNNs OpenCV (DE-588)1038770092 gnd Python Programmiersprache (DE-588)4434275-5 gnd Maschinelles Sehen (DE-588)4129594-8 gnd Deep learning (DE-588)1135597375 gnd |
| subject_GND | (DE-588)1038770092 (DE-588)4434275-5 (DE-588)4129594-8 (DE-588)1135597375 |
| title | Learn computer vision using OpenCV with deep learning CNNs and RNNs |
| title_auth | Learn computer vision using OpenCV with deep learning CNNs and RNNs |
| title_exact_search | Learn computer vision using OpenCV with deep learning CNNs and RNNs |
| title_full | Learn computer vision using OpenCV with deep learning CNNs and RNNs Sunila Gollapudi |
| title_fullStr | Learn computer vision using OpenCV with deep learning CNNs and RNNs Sunila Gollapudi |
| title_full_unstemmed | Learn computer vision using OpenCV with deep learning CNNs and RNNs Sunila Gollapudi |
| title_short | Learn computer vision using OpenCV |
| title_sort | learn computer vision using opencv with deep learning cnns and rnns |
| title_sub | with deep learning CNNs and RNNs |
| topic | OpenCV (DE-588)1038770092 gnd Python Programmiersprache (DE-588)4434275-5 gnd Maschinelles Sehen (DE-588)4129594-8 gnd Deep learning (DE-588)1135597375 gnd |
| topic_facet | OpenCV Python Programmiersprache Maschinelles Sehen Deep learning |
| work_keys_str_mv | AT gollapudisunila learncomputervisionusingopencvwithdeeplearningcnnsandrnns |