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Deep Convolutional Neural Network for The Prognosis of Diabetic Retinopathy

neural network and visualizations techniques, this work develops a prognosis system used to automatically detect the diabetic retinopathy disease;

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Diabetic Retinopathy

Diabetes mellitus is one of the leading causes of blindness worldwide, with diabetic retinopathy (DR) remaining the most common cause;

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Deep Neural Networks in a Mathematical Framework

This SpringerBrief describes how to build a rigorous end-to-end mathematical framework for deep neural networks. The authors provide tools;

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Deep Learning from Scratch Building with Python from First Principles

With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many;

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Diabetic Retinopathy

at the same time giving the necessary information for updated management of diabetic retinopathy. Diabetic Retinopathy will be especially;

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Churchill's Pocketbook Of Diabetes

, prognosis and consequences for their lifestyle; offers practical and accessible advice on all aspects of the condition from presentation and;

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Deep Learning for Natural Language Processing

Gain the knowledge of various deep neural network architectures and their application areas to conquer your NLP issues. Key Features Gain;

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Deep Learning with PyTorch Quick Start Guide

Introduction to deep learning and PyTorch by building a convolutional neural network and recurrent neural network for real-world use cases;

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Advanced Deep Learning with R

learning book starts by covering the essential deep learning techniques and concepts for prediction and classification. You will learn about neural;

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Neural Information Processing

follows: adversarial networks and learning; convolutional neural networks; deep neural networks; embeddings and feature fusion; human centred;

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Diabetic Retinopathy

care by increasing their understanding of diabetic retinopathy and its implications for overall diabetes care. It includes a description;

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Diabetic Retinopathy

Diabetic Retinopathy is a concise guide to the condition caused by complications of diabetes, which can eventually lead to blindness. The;

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Hardware Accelerator Systems for Artificial Intelligence and Machine Learning

, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and;

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The Deep Learning with PyTorch Workshop

complexity of neural network architectures. The Deep Learning with PyTorch Workshop starts with an introduction to deep learning and its applications;

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Convolutional Neural Networks in Visual Computing

neural networks (CNN) from scratch. The book focuses explicitly on convolutional neural networks, filtering out other material that co-occur;

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Convolutional Neural Networks in Visual Computing

neural networks (CNN) from scratch. The book focuses explicitly on convolutional neural networks, filtering out other material that co-occur;

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Retinopathy

, produce, and therefore are correlated to, retinal anomalies. In this book, the authors present current research in the study of retinopathy;

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Visual Dysfunction in Diabetes

treatments for diabetic retinopathy are to be found and applied. Developed by a renowned group of authorities, Visual Dysfunction in Diabetes: The;

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Hands-On Deep Learning with TensorFlow

about convolutional neural networks, and logistic regression while training models for deep learning to gain key insights into your data;

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Tree-Based Convolutional Neural Networks

This book proposes a novel neural architecture, tree-based convolutional neural networks (TBCNNs),for processing tree-structured data;

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Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide

as convolutional and recurrent neural networks. This book will help you understand the basics of deep learning. You will learn how to use;

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Hands-on Machine Learning with Python

third section explains complex neural network architectures with details on internal working and implementation of convolutional neural networks;

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Mastering PyTorch

overview of PyTorch and explores using convolutional neural network (CNN) architectures for image classification. You'll then work with recurrent;

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Small-Gauge Vitrectomy for Diabetic Retinopathy

This book describes step by step how to operate on the patient with diabetic retinopathy. After thorough explanation of surgical planning;

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Deep Learning and Convolutional Neural Networks for Medical Image Computing

in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural;

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Deep Learning with Hadoop

the challenges of implementing distributed deep learning with Hadoop and how to overcome it * Implement Convolutional Neural Network (CNN;

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