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Convolutional Neural Networks for Medical Image Processing Applications, Cootsona, Greg


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Цена: 148010.00T
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Автор: Cootsona, Greg
Название:  Convolutional Neural Networks for Medical Image Processing Applications
ISBN: 9781032104003
Издательство: Taylor&Francis
Классификация:











ISBN-10: 1032104007
Обложка/Формат: Hardback
Страницы: 268
Вес: 0.53 кг.
Дата издания: 23.12.2022
Язык: English
Иллюстрации: 44 tables, black and white; 52 line drawings, black and white; 43 halftones, black and white; 95 illustrations, black and white
Размер: 162 x 240 x 22
Читательская аудитория: General (us: trade)
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Поставляется из: Европейский союз
Описание: This book contains applications of CNN methods. The content is quite extensive, including the application of different CNN methods to various medical image processing problems. Readers will be able to analyze the effects of CNN methods presented in the book in medical applications.

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: 149060.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
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: 149060.00 T
Наличие на складе: Поставка под заказ.
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.

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: 79190.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
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.

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: 46570.00 T
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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.

Convolutional neural networks with swift for tensorflow

Автор: Koonce, Brett
Название: Convolutional neural networks with swift for tensorflow
ISBN: 1484261674 ISBN-13(EAN): 9781484261675
Издательство: Springer
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Цена: 51230.00 T
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Описание:
Chapter 1: MNIST: 1D Neural Network
Chapter 2: MNIST: 2D Neural Network
Chapter 3: CIFAR: 2D Nueral Network with Blocks
Chapter 4: VGG Network
Chapter 5: Resnet 34
Chapter 6: Resnet 50
Chapter 7: SqueezeNet

Chapter 8: MobileNrt v1
Chapter 9: MobileNet v2
Chapter 10: Evolutionary Strategies
Chapter 11: MobileNet v3
Chapter 12: Bag of Tricks
Chapter 13: MNIST Revisited
Chapter 14: You are Here

Convolutional Neural Networks In Vi

Автор: Venkatesan, Ragav,
Название: Convolutional Neural Networks In Vi
ISBN: 1498770398 ISBN-13(EAN): 9781498770392
Издательство: Taylor&Francis
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Цена: 168430.00 T
Наличие на складе: Невозможна поставка.
Описание: This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner`s guide to engineers or students who want to have a quick start on learning and/or building deep learning systems.

A Guide to Convolutional Neural Networks for Computer Vision

Автор: Salman Khan, Hossein Rahmani, Syed Afaq Ali Shah, Mohammed Bennamoun
Название: A Guide to Convolutional Neural Networks for Computer Vision
ISBN: 1681732785 ISBN-13(EAN): 9781681732787
Издательство: Mare Nostrum (Eurospan)
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Цена: 102570.00 T
Наличие на складе: Невозможна поставка.
Описание: Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision.This self-contained guide will benefit those who seek to both understand the theory behind CNNs and to gain hands-on experience on the application of CNNs in computer vision. It provides a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs. The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision. Further, this text describes and discusses case studies that are related to the application of CNN in computer vision, including image classification, object detection, semantic segmentation, scene understanding, and image generation.This book is ideal for undergraduate and graduate students, as no prior background knowledge in the field is required to follow the material, as well as new researchers, developers, engineers, and practitioners who are interested in gaining a quick understanding of CNN models.

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: 51230.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
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
Рейтинг:
Цена: 40450.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
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!

Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Constrained IoT Edge Devices

Автор: Abich
Название: Early Soft Error Reliability Assessment of Convolutional Neural Networks Executing on Resource-Constrained IoT Edge Devices
ISBN: 3031185986 ISBN-13(EAN): 9783031185984
Издательство: Springer
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Цена: 74530.00 T
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Описание: This book describes an extensive and consistent soft error assessment of convolutional neural network (CNN) models from different domains through more than 14.8 million fault injections, considering different precision bit-width configurations, optimization parameters, and processor models. The authors also evaluate the relative performance, memory utilization, and soft error reliability trade-offs analysis of different CNN models considering a compiler-based technique w.r.t. traditional redundancy approaches.

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: 107190.00 T
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Introduction to Convolutional Codes with Applications

Автор: Ajay Dholakia
Название: Introduction to Convolutional Codes with Applications
ISBN: 1461361680 ISBN-13(EAN): 9781461361688
Издательство: Springer
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Цена: 121890.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction to Convolutional Codes with Applications is an introduction to the basic concepts of convolutional codes, their structure and classification, various error correction and decoding techniques for convolutionally encoded data, and some of the most common applications.


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