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

Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer;

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Mastering OpenCV 4 with Python

Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web;

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TensorFlow 2.0 Computer Vision Cookbook

for images using CNNs and RNNs Who this book is forThis book is for computer vision developers and engineers, as well as deep learning;

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Machine Learning for OpenCV 4

machine learning for building intelligent computer vision applications with OpenCV 4. What you will learn Understand the core machine learning;

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OpenCV

to teach the following topics. First, we will learn how to get started with OpenCV and OpenCV3's Python API, and develop a computer vision;

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Practical Computer Vision Applications Using Deep Learning with CNNs

Will Learn Understand how ANNs and CNNs work Create computer vision applications and CNNs from scratch using Python Follow a deep learning;

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Learning OpenCV 3 Computer Vision with Python -

Unleash the power of computer vision with Python using OpenCV About This Book * Create impressive applications with OpenCV and Python;

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The Deep Learning Workshop

Features Understand how to implement deep learning with TensorFlow and Keras Learn the fundamentals of computer vision and image recognition;

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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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Building Computer Vision Projects with OpenCV 4 and C++

and want to develop interesting computer vision applications with OpenCV, this Learning Path is for you. Prior knowledge of C++ and;

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The The Computer Vision Workshop

Explore the potential of deep learning techniques in computer vision applications using the Python ecosystem, and build real-time systems;

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OpenCV 4 with Python Blueprints

Get to grips with traditional computer vision algorithms and deep learning approaches, and build real-world applications with OpenCV and;

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Machine Learning for OpenCV

Learn * Explore and make effective use of OpenCV's machine learning module * Learn deep learning for computer vision with Python * Master;

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Deep Learning with R Cookbook

. What you will learn Work with different datasets for image classification using CNNs Apply transfer learning to solve complex computer vision;

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OpenCV 4 Computer Vision Application Programming Cookbook

applications Build computer vision algorithms with machine learning capabilities Book DescriptionOpenCV is an image and video processing library used;

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OpenCV with Python Blueprints

Design and develop advanced computer vision projects using OpenCV with Python About This Book * Program advanced computer vision;

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Hands-On GPU-Accelerated Computer Vision with OpenCV and CUDA

range of industries, and OpenCV is the most widely chosen tool for computer vision with its ability to work in multiple programming languages;

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Practical Machine Learning and Image Processing

using the OpenCV library Use TensorFlow, scikit-learn, NumPy, and other libraries Work with machine learning and deep learning algorithms;

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OpenCV 3 Computer Vision with Python Cookbook

learning and neural networks. By the end of the book, you'll be able to apply your skills in OpenCV to create computer vision applications;

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The Deep Learning with PyTorch Workshop

neural networks (ANNs) Handle computer vision problems with convolutional neural networks (CNNs) Perform language translation tasks using;

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Learning OpenCV 4 Computer Vision with Python 3

-world computer vision projects. What you will learn Install and familiarize yourself with OpenCV 4's Python 3 bindings Understand image;

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Artificial Intelligence, Machine Learning, and Deep Learning

learning architectures such as CNNs, RNNs,LSTMs, and auto encoders. Keras-based code samples are included to supplementthe theoretical discussion;

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PyTorch Deep Learning Hands-On

major deep learning architectures in PyTorch. It covers neural networks, computer vision, CNNs, natural language processing (RNN), GANs, and;

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OpenCV 3 Computer Vision Application Programming Cookbook - Third Edition

* Master fundamental concepts in computer vision and image processing * Learn about the important classes and functions of OpenCV with complete;

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Artificial Vision and Language Processing for Robotics

robots. You'll compare different methods used to work with robots and explore computer vision, its algorithms, and limits. You'll then learn how;

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Hands-On Convolutional Neural Networks with TensorFlow

Learn how to apply TensorFlow to a wide range of deep learning and Machine Learning problems with this practical guide on training CNNs for;

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Practical Machine Learning and Image Processing

biggest computer vision library: OpenCV. Yoüll see the OpenCV algorithms and how to use them for image processing. The next section looks at;

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