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Neural Network Computer Vision with OpenCV 5
Build computer vision solutions using Python and DNN module (English Edition)
Taschenbuch von Gopi Krishna Nuti
Sprache: Englisch

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Beschreibung
Unlocking computer vision with Python and OpenCV

¿DESCRIPTION
Neural Network Computer Vision with OpenCV equips you with professional skills and knowledge to build intelligent vision systems using OpenCV. It creates a sequential pathway for understanding morphological operations, edge and corner detection, object localization, image classification, segmentation, and advanced applications like face detection and recognition, and optical character recognition.

This book offers a practical roadmap to explore the nuances of image processing with detailed discussions on each topic, supported by hands-on Python code examples. The readers will learn the basics of neural networks, deep learning and CNNs by using deep learning frameworks like Keras, Tensorflow, PyTorch, Caffe etc. They will be able to utilize OpenCV DNN module to classify images by using models like Inception V3, Resnet 101, Mobilenet V2. Moreover, the book will help to successfully Implement object detection using YOLOv3, SSD and R-CNN models. The character detection and recognition models are also covered in depth with code examples.

You will gain a deeper understanding of how these techniques impact real-world scenarios and learn to harness the potential of Python and OpenCV to solve complex problems. Whether you are building intelligent systems, automating processes, or working on image-related projects, this book equips you with the skills to revolutionize your approach to visual data.

WHAT YOU WILL LEARN
¿ Acquire expertise in image manipulation techniques.
¿ Apply knowledge to practical scenarios in computer vision.
¿ Implement robust systems for face detection and recognition.
¿ Enhance projects with accurate object localization capabilities.
¿ Extract text information from images effectively.

WHO THIS BOOK IS FOR
This book is designed for those with basic Python skills, from beginners to intermediate-level readers. Whether you are building intelligent robots that perceive their surroundings or crafting advanced vision systems for object detection and image analysis, this book will equip you with the tools and skills to push the boundaries of AI perception.
Unlocking computer vision with Python and OpenCV

¿DESCRIPTION
Neural Network Computer Vision with OpenCV equips you with professional skills and knowledge to build intelligent vision systems using OpenCV. It creates a sequential pathway for understanding morphological operations, edge and corner detection, object localization, image classification, segmentation, and advanced applications like face detection and recognition, and optical character recognition.

This book offers a practical roadmap to explore the nuances of image processing with detailed discussions on each topic, supported by hands-on Python code examples. The readers will learn the basics of neural networks, deep learning and CNNs by using deep learning frameworks like Keras, Tensorflow, PyTorch, Caffe etc. They will be able to utilize OpenCV DNN module to classify images by using models like Inception V3, Resnet 101, Mobilenet V2. Moreover, the book will help to successfully Implement object detection using YOLOv3, SSD and R-CNN models. The character detection and recognition models are also covered in depth with code examples.

You will gain a deeper understanding of how these techniques impact real-world scenarios and learn to harness the potential of Python and OpenCV to solve complex problems. Whether you are building intelligent systems, automating processes, or working on image-related projects, this book equips you with the skills to revolutionize your approach to visual data.

WHAT YOU WILL LEARN
¿ Acquire expertise in image manipulation techniques.
¿ Apply knowledge to practical scenarios in computer vision.
¿ Implement robust systems for face detection and recognition.
¿ Enhance projects with accurate object localization capabilities.
¿ Extract text information from images effectively.

WHO THIS BOOK IS FOR
This book is designed for those with basic Python skills, from beginners to intermediate-level readers. Whether you are building intelligent robots that perceive their surroundings or crafting advanced vision systems for object detection and image analysis, this book will equip you with the tools and skills to push the boundaries of AI perception.
Über den Autor
Gopi Krishna Nuti is an experienced professional with 21 years of experience in IT industry. He has done his B. Tech in Computer Science from Andhra University, M.S in Business Analytics from State University of New York at Buffalo and an Executive MBA from Amrita University, Bengaluru. He has worked extensively in analytics and software development projects and has delivered award winning products and solutions.
Details
Erscheinungsjahr: 2023
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
ISBN-13: 9789355516961
ISBN-10: 9355516967
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Nuti, Gopi Krishna
Hersteller: BPB Publications
Maße: 235 x 191 x 14 mm
Von/Mit: Gopi Krishna Nuti
Erscheinungsdatum: 30.12.2023
Gewicht: 0,503 kg
Artikel-ID: 128259049
Über den Autor
Gopi Krishna Nuti is an experienced professional with 21 years of experience in IT industry. He has done his B. Tech in Computer Science from Andhra University, M.S in Business Analytics from State University of New York at Buffalo and an Executive MBA from Amrita University, Bengaluru. He has worked extensively in analytics and software development projects and has delivered award winning products and solutions.
Details
Erscheinungsjahr: 2023
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
ISBN-13: 9789355516961
ISBN-10: 9355516967
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Nuti, Gopi Krishna
Hersteller: BPB Publications
Maße: 235 x 191 x 14 mm
Von/Mit: Gopi Krishna Nuti
Erscheinungsdatum: 30.12.2023
Gewicht: 0,503 kg
Artikel-ID: 128259049
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