Learn Computer Vision Using OpenCV
Apress (Verlag)
978-1-4842-4260-5 (ISBN)
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 Learn
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
Who This Book Is ForThose who have a basic understanding of machine learning and Python and are looking to learn computer vision and its applications.
Sunila Gollapudi has over 17 years of experience in developing, designing and architecting data-driven solutions with a focus on the banking and financial services sector. She is currently working at Broadridge, India as vice president. She's played various roles as chief architect, big data and AI evangelist, and mentor. She has been a speaker at various conferences and meetups on Java and big data technologies. Her current big data and data science expertise includes Hadoop, Greenplum, MarkLogic, GemFire, ElasticSearch, Apache Spark, Splunk, R, Julia, Python (scikit-learn), Weka, MADlib, Apache Mahout, and advanced analytics techniques such as deep learning, computer vision, reinforcement, and ensemble learning.
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.
Erscheinungsdatum | 10.05.2019 |
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Zusatzinfo | 61 Illustrations, color; 27 Illustrations, black and white; XX, 151 p. 88 illus., 61 illus. in color. |
Verlagsort | Berkley |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge |
Mathematik / Informatik ► Informatik ► Software Entwicklung | |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
Schlagworte | Artificial Intelligence • computer vision • Deep learning • Image Segmentation • Object detection • Open CV • Python |
ISBN-10 | 1-4842-4260-2 / 1484242602 |
ISBN-13 | 978-1-4842-4260-5 / 9781484242605 |
Zustand | Neuware |
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