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Deep Learning for Vision Systems

, and much, much more. Amazing new computer vision applications are developed every day, thanks to rapid advances in AI and deep learning (DL;

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Learn Computer Vision Using Opencv: With Deep Learning Cnns and Rnns

Discover the deep learning techniques required to build computer vision applications Build complex computer vision applications using the latest;

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Domain Adaptation in Computer Vision with Deep Learning

This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the;

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Deep Learning for Computer Vision

kinds of deep learning model from scratch to solve specific problems in Computer Vision Combine the power of Python, Keras, and TensorFlow to;

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Deep Learning in Computer Vision

Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions;

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Mastering OpenCV 4 with Python

Create computer vision and deep learning web applications Who this book is forThis book is designed for computer vision developers, engineers;

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Computer Vision Metrics

-of-the-art survey for fundamental computer vision methods and deep learning. With over 800 essential references, as well as chapter-by-chapter;

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Computer Analysis of Images and Patterns

and Patterns, CAIP 2019, held in Salerno, Italy, in September 2019: First Workshop on Deep-learning based Computer Vision for UAV, DL-UAV 2019;

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Deep Learning in Computer Vision: Principles and Applications

Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions;

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Practical Computer Vision Applications Using Deep Learning with CNNs

Deploy deep learning applications into production across multiple platforms. You will work on computer vision applications that use the;

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R Deep Learning Essentials

computer vision and text Apply deep learning techniques in cloud for large-scale processing Build, train, and optimize neural network models on a;

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Convective Cell Tracking through Deep Learning based Computer Vision

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Deep Learning in Mining of Visual Content

in Digital form is constantly growing in volume. In such active domains as Computer Vision and Robotics visual information understanding is based on;

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TensorFlow 2.0 Computer Vision Cookbook

machine learning and deep learning techniques Key Features Develop, train, and use deep learning algorithms for computer vision tasks using;

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Deep Learning through Sparse and Low-Rank Modeling

variety of applications in computer vision, machine learning, signal processing, and data mining. This book will be highly useful for;

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Computer Vision ACCV 2020

vision Part IV: deep learning for computer vision, generative models for computer vision Part V: face, pose, action, and gesture; video analysis;

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Computer Vision ACCV 2020

vision Part IV: deep learning for computer vision, generative models for computer vision Part V: face, pose, action, and gesture; video analysis;

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Computer Vision ACCV 2020

vision Part IV: deep learning for computer vision, generative models for computer vision Part V: face, pose, action, and gesture; video analysis;

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Computer Vision ACCV 2020

vision Part IV: deep learning for computer vision, generative models for computer vision Part V: face, pose, action, and gesture; video analysis;

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Computer Vision Projects with PyTorch

will be able to build your own computer vision projects using transfer learning and PyTorch. What You Will Learn Solve problems;

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Deep Learning

, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones;

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Computer Vision Projects with OpenCV and Python 3

learning developers who wish to build exciting Computer Vision projects using the power of machine learning and OpenCV will find this book useful;

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Mastering Computer Vision with TensorFlow 2.x

analysis. You'll start with the key principles of computer vision and deep learning to build a solid foundation, before covering neural network;

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Pattern Recognition and Computer Vision

Recognition and Computer Vision, PRCV 2021, held in Beijing, China, in October-November 2021. The 201 full papers presented were carefully;

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Challenges and Applications for Implementing Machine Learning in Computer Vision

efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is a;

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Challenges and Applications for Implementing Machine Learning in Computer Vision

efficiency of current methods that enable machines to see. Challenges and Applications for Implementing Machine Learning in Computer Vision is a;

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Machine Learning for OpenCV 4

understanding the new features and setting up OpenCV 4 to build your computer vision applications. You will explore the fundamentals of machine learning;

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