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Deep Learning for Vision Systems

). Deep Learning for Vision Systems teaches you the concepts and tools for building intelligent, scalable computer vision systems that can;

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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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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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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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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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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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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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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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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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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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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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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 OpenCV and Python 3

Computer Vision projects tackling real-world problems. With the help of this book, you will learn how to set up Anaconda and Python for the major;

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Convective Cell Tracking through Deep Learning based Computer Vision

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Computer Vision Projects with PyTorch

Design and develop end-to-end, production-grade computer vision projects for real-world industry problems. This book discusses computer;

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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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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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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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Machine Learning for OpenCV 4

how they can be used for object detection computer vision operations. You will then delve into deep learning and ensemble learning, and;

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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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Deep Learning with JavaScript

cases and in-depth instruction for deep learning apps in JavaScript in your browser or on Node. Deploying computer vision, audio, and;

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Applied Deep Learning and Computer Vision for Self-Driving Cars

This book teaches you the different techniques and methodologies associated while implementing deep learning solutions in self-driving cars;

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