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(Ebook) Building Computer Vision Applications Using Artificial Neural Networks: With Step-by-Step Examples in OpenCV and TensorFlow with Python by Shamshad Ansari ISBN 9781484258866, 148425886X

  • SKU: EBN-50195836
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Instant download (eBook) Building Computer Vision Applications Using Artificial Neural Networks: With Step-by-Step Examples in OpenCV and TensorFlow with Python after payment.
Authors:Shamshad Ansari
Year:2020
Editon:1
Publisher:Apress
Language:english
File Size:15.45 MB
Format:pdf
ISBNS:9781484258866, 148425886X
Categories: Ebooks

Product desciption

(Ebook) Building Computer Vision Applications Using Artificial Neural Networks: With Step-by-Step Examples in OpenCV and TensorFlow with Python by Shamshad Ansari ISBN 9781484258866, 148425886X

Apply computer vision and machine learning concepts in developing business and industrial applications ​using a practical, step-by-step approach.  The book comprises four main sections starting with setting up your programming environment and configuring your computer with all the prerequisites to run the code examples. Section 1 covers the basics of image and video processing with code examples of how to manipulate and extract useful information from the images. You will mainly use OpenCV with Python to work with examples in this section.  Section 2 describes machine learning and neural network concepts as applied to computer vision. You will learn different algorithms of the neural network, such as convolutional neural network (CNN), region-based convolutional neural network (R-CNN), and YOLO. In this section, you will also learn how to train, tune, and manage neural networks for computer vision. Section 3 provides step-by-step examples of developing business and industrial applications, such as facial recognition in video surveillance and surface defect detection in manufacturing.  The final section is about training neural networks involving a large number of images on cloud infrastructure, such as Amazon AWS, Google Cloud Platform, and Microsoft Azure. It walks you through the process of training distributed neural networks for computer vision on GPU-based cloud infrastructure. What You Will Learn• Employ image processing, manipulation, and feature extraction techniques• Work with various deep learning algorithms for computer vision• Train, manage, and tune hyperparameters of CNNs and object detection models, such as R-CNN, SSD, and YOLO• Build neural network models using Keras and TensorFlow• Discover best practices when implementing computer vision applications in business and industry• Train distributed models on GPU-based cloud infrastructure
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