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Medical Images Classification Using Deep Learning

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Medical Images Classification Using Deep Learning

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Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis

medical images. Examines the methodology of classification of medical images that covers the taxonomy of both supervised and;

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Deep Learning for Chest Radiographs

, implementation, and application of deep-learning techniques for medical images such as transfer learning using pretrained CNNs, series networks, directed;

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Deep Network Design for Medical Image Computing

classification, detection, segmentation, registration, reconstruction and synthesis of medical images;

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Deep Learning in Healthcare

This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and;

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Deep Learning in Healthcare

This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and;

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Hands-On Deep Learning for Images with TensorFlow

Build an effective image classification system using the power of CNNs Leverage TensorFlow's capabilities to perform efficient deep learning;

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Advanced Deep Learning with R

Discover best practices for choosing, building, training, and improving deep learning models using Keras-R, and TensorFlow-R libraries Key;

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Deep Learning in Medical Image Analysis

lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and;

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Deep Learning Applications

ICMLA 2018), focusing on use of deep learning technology in application like game playing, medical applications, video analytics, regression;

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Computer Vision Projects with OpenCV and Python 3

Features Implement image classification and object detection using machine learning and deep learning Perform image classification, object;

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Data Analytics in Biomedical Engineering and Healthcare

Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning;

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MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition

MatConvNet deep learning. Featuring research on topics such as medical image diagnosis, convolutional neural networks, and character classification;

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MatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition

MatConvNet deep learning. Featuring research on topics such as medical image diagnosis, convolutional neural networks, and character classification;

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Deep Learning for Biomedical Applications

This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the;

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Deep Learning for the Life Sciences

deep learning to analyze microscopic images Analyze medical scans using deep learning techniques Learn about variational autoencoders and;

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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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Hands-On Image Processing with Python

enhancement, filtering, segmentation, object detection, and classification. We will be able to use machine learning models using the scikit-learn;

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The Deep Learning Workshop

synthesized images Who this book is for If you are interested in machine learning and want to create and train deep learning models using;

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Deep Learning for Computer Vision

build deep learning models for object detection, image classification, similarity learning, image captioning, and more Includes tips on;

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AI and Deep Learning in Biometric Security

understanding deep learning concepts for biometrics authentication approaches and presents an analysis of biometric images under various environmental;

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Deep Learning for Data Analytics

and Challenges provides readers with a focused approach for the design and implementation of deep learning concepts using data analytics;

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Java Deep Learning Cookbook

in Java Model neural networks using datasets containing images, text, and time-series data Book DescriptionJava is one of the most widely used;

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Medical Imaging

book discusses varied topics pertaining to advanced or up-to-date techniques in medical imaging using artificial intelligence (AI), image;

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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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Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification

focus on using large range of fuzzy classification algorithms for remote sensing images; discuss ANN, CNN, RNN, and hybrid learning;

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