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Deep Convolutional Neural Network for The Prognosis of Diabetic Retinopathy, Shanthini


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Автор: Shanthini
Название:  Deep Convolutional Neural Network for The Prognosis of Diabetic Retinopathy
ISBN: 9789811938764
Издательство: Springer
Классификация:




ISBN-10: 9811938768
Обложка/Формат: Hardback
Страницы: 75
Вес: 0.32 кг.
Дата издания: 08.09.2022
Серия: Series in BioEngineering
Язык: English
Издание: 1st ed. 2023
Иллюстрации: 29 illustrations, color; 12 illustrations, black and white; ix, 75 p. 41 illus., 29 illus. in color.
Размер: 235 x 155
Читательская аудитория: Professional & vocational
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book discusses a detailed overview of diabetic retinopathy, symptoms, causes, and screening methodologies. Using a deep convolution neural network and visualizations techniques, this work develops a prognosis system used to automatically detect the diabetic retinopathy disease from captured retina images and help improve the prediction rate of diagnosis. This book gives the readers an understanding of the diabetic retinopathy disease and recognition process that helps to improve the clinical analysis efficiency. It caters to general ophthalmologists and optometrists, diabetologists, and internists who encounter diabetic patients and most prevalent retinal diseases daily.
Дополнительное описание: Introduction.- Chapter 1 - Background of diabetic retinopathy.- Chapter 2 - Classification of diabetic retinopathy.- Chapter 3 - Deep convolutional neural network architecture.- Chapter 4 - Deep convolutional neural network applications and visualization



Convolutional Neural Networks for Medical Applications

Автор: Teoh
Название: Convolutional Neural Networks for Medical Applications
ISBN: 9811988137 ISBN-13(EAN): 9789811988134
Издательство: Springer
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Цена: 6986.00 р.
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Описание: Convolutional Neural Networks for Medical Applications consists of research investigated by the author, containing state-of-the-art knowledge, authored by Dr Teoh Teik Toe, in applying Convolutional Neural Networks (CNNs) to the medical imagery domain. This book will expose researchers to various applications and techniques applied with deep learning on medical images, as well as unique techniques to enhance the performance of these networks.Through the various chapters and topics covered, this book provides knowledge about the fundamentals of deep learning to a common reader while allowing a research scholar to identify some futuristic problem areas. The topics covered include brain tumor classification, pneumonia image classification, white blood cell classification, skin cancer classification and diabetic retinopathy detection. The first chapter will begin by introducing various topics used in training CNNs to help readers with common concepts covered across the book. Each chapter begins by providing information about the disease, its implications to the affected and how the use of CNNs can help to tackle issues faced in healthcare. Readers would be exposed to various performance enhancement techniques, which have been tried and tested successfully, such as specific data augmentations and image processing techniques utilized to improve the accuracy of the models.

Encyclopedia of Diabetic Retinopathy

Автор: Gipe Abigail
Название: Encyclopedia of Diabetic Retinopathy
ISBN: 1632421356 ISBN-13(EAN): 9781632421357
Издательство: Неизвестно
Цена: 28324.00 р.
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Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics

Автор: Le Lu
Название: Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics
ISBN: 3030139689 ISBN-13(EAN): 9783030139681
Издательство: Springer
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Цена: 22359.00 р.
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Описание: This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases.

Deep Learning and Convolutional Neural Networks for Medical Image Computing

Автор: Le Lu; Yefeng Zheng; Gustavo Carneiro; Lin Yang
Название: Deep Learning and Convolutional Neural Networks for Medical Image Computing
ISBN: 3319827138 ISBN-13(EAN): 9783319827131
Издательство: Springer
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Цена: 22359.00 р.
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Описание: This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.

Advanced Applied Deep Learning

Автор: Umberto Michelucci
Название: Advanced Applied Deep Learning
ISBN: 1484249755 ISBN-13(EAN): 9781484249758
Издательство: Springer
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Цена: 6288.00 р.
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Описание: Develop and optimize deep learning models with advanced architectures. This book teaches you the intricate details and subtleties of the algorithms that are at the core of convolutional neural networks. In Advanced Applied Deep Learning, you will study advanced topics on CNN and object detection using Keras and TensorFlow. Along the way, you will look at the fundamental operations in CNN, such as convolution and pooling, and then look at more advanced architectures such as inception networks, resnets, and many more. While the book discusses theoretical topics, you will discover how to work efficiently with Keras with many tricks and tips, including how to customize logging in Keras with custom callback classes, what is eager execution, and how to use it in your models. Finally, you will study how object detection works, and build a complete implementation of the YOLO (you only look once) algorithm in Keras and TensorFlow. By the end of the book you will have implemented various models in Keras and learned many advanced tricks that will bring your skills to the next level.

What You Will LearnSee how convolutional neural networks and object detection workSave weights and models on diskPause training and restart it at a later stage Use hardware acceleration (GPUs) in your codeWork with the Dataset TensorFlow abstraction and use pre-trained models and transfer learningRemove and add layers to pre-trained networks to adapt them to your specific projectApply pre-trained models such as Alexnet and VGG16 to new datasets Who This Book Is ForScientists and researchers with intermediate-to-advanced Python and machine learning know-how. Additionally, intermediate knowledge of Keras and TensorFlow is expected.
Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics

Автор: Lu Le, Wang Xiaosong, Carneiro Gustavo
Название: Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics
ISBN: 3030139719 ISBN-13(EAN): 9783030139711
Издательство: Springer
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Цена: 11878.00 р.
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Описание: This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases.

Guide to Convolutional Neural Networks

Автор: Hamed Habibi Aghdam; Elnaz Jahani Heravi
Название: Guide to Convolutional Neural Networks
ISBN: 3319861905 ISBN-13(EAN): 9783319861906
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This must-read text/reference introduces the fundamental concepts of convolutional neural networks (ConvNets), offering practical guidance on using libraries to implement ConvNets in applications of traffic sign detection and classification.

Iot-enabled convolutional neural networks: techniques and applications

Название: Iot-enabled convolutional neural networks: techniques and applications
ISBN: 877022725X ISBN-13(EAN): 9788770227254
Издательство: Taylor&Francis
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Цена: 16078.00 р.
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Deep Belief Nets in C++ and CUDA C: Volume 3

Автор: Masters
Название: Deep Belief Nets in C++ and CUDA C: Volume 3
ISBN: 148423720X ISBN-13(EAN): 9781484237205
Издательство: Springer
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Цена: 8384.00 р.
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Описание:

Discover the essential building blocks of a common and powerful form of deep belief network: convolutional nets. This book shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a ‘thought process’ that is capable of learning abstract concepts built from simpler primitives. These models are especially useful for image processing applications.
At each step Deep Belief Nets in C++ and CUDA C: Volume 3 presents intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. Source code for all routines presented in the book, and the executable CONVNET program which implements these algorithms, are available for free download.
What You Will Learn
Discover convolutional nets and how to use themBuild deep feedforward nets using locally connected layers, pooling layers, and softmax outputsMaster the various programming algorithms requiredCarry out multi-threaded gradient computations and memory allocations for this threadingWork with CUDA code implementations of all core computations, including layer activations and gradient calculationsMake use of the CONVNET program and manual to explore convolutional nets and case studies
Who This Book Is For
Those who have at least a basic knowledge of neural networks and some prior programming experience, although some C++ and CUDA C is recommended.
Diabetic Retinopathy

Автор: S. Riaskoff
Название: Diabetic Retinopathy
ISBN: 9061935547 ISBN-13(EAN): 9789061935544
Издательство: Springer
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Цена: 12157.00 р.
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Описание: The evaluation of diabetic retinopathy is often difficult, because the clinical picture is complex due to the mUltiplicity of symptoms. Standard photograph number one stands for the moderate (grade 1 ) manifestation and standard photograph numbertwo stands forthe marked (grade 2) manifestation of the symptom.

Tree-Based Convolutional Neural Networks

Автор: Lili Mou; Zhi Jin
Название: Tree-Based Convolutional Neural Networks
ISBN: 9811318697 ISBN-13(EAN): 9789811318696
Издательство: Springer
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Цена: 7685.00 р.
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Описание: This book proposes a novel neural architecture, tree-based convolutional neural networks (TBCNNs),for processing tree-structured data. TBCNNsare related to existing convolutional neural networks (CNNs) and recursive neural networks (RNNs), but they combine the merits of both: thanks to their short propagation path, they are as efficient in learning as CNNs; yet they are also as structure-sensitive as RNNs. In this book, readers will also find a comprehensive literature review of related work, detailed descriptions of TBCNNs and their variants, and experiments applied to program analysis and natural language processing tasks. It is also an enjoyable read for all those with a general interest in deep learning.

Hands-on Convolutional Neural Networks with Tensorflow

Автор: Zafar Iffat, Tzanidou Giounona, Burton Richard
Название: Hands-on Convolutional Neural Networks with Tensorflow
ISBN: 1789130336 ISBN-13(EAN): 9781789130331
Издательство: Неизвестно
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Цена: 6068.00 р.
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Описание: Convolutional Neural Networks (CNN) are one of the most popular architectures used in computer vision apps. This book is an introduction to CNNs through solving real-world problems in deep learning while teaching you their implementation in popular Python library - TensorFlow. By the end of the book, you will be training CNNs in no time!


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