Artículo: AMZ-B0BLQK2M9N

Convolutional Neural Networks for Medical Image Processing Applications

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The rise in living standards increases the expectation of people in almost every field. At the forefront is health. Over the past few centuries, there have been major developments in healthcare. Medical device technology and developments in artificial intelligence (AI) are among the most important ones. The improving technology and our ability to harness the technology effectively by means such as AI have led to unprecedented advances, resulting in early diagnosis of diseases. AI algorithms enable the fast and early evaluation of images from medical devices to maximize the benefits. While developments in the field of AI were quickly adapted to the field of health, in some cases this contributed to the formation of innovative artificial intelligence algorithms. Today, the most effective artificial intelligence method is accepted as deep learning. Convolutional neural network (CNN) architectures are deep learning algorithms used for image processing. 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.

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Fundamentals of Convolutional Coding (IEEE Series on Digital & Mobile Communication)

CONVOLUTIONAL NEURAL NETWORKS Examples with MATLAB

Advanced Applied Deep Learning: Convolutional Neural Networks and Object Detection

Practical Convolutional Neural Networks: Implement advanced deep learning models using Python

Convolutional Neural Networks: 33 Comprehensively Commented Python Implementations of Convolutional Neural Networks (Stochastic Sorcerers)

Guide to Convolutional Neural Networks: A Practical Application to Traffic-Sign Detection and Classification

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Convolutional Neural Networks and Recurrent Neural Networks: Convolutional Neural Networks and Recurrent Neural Networks

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Convolutional Coding: Fundamentals and Applications (Artech House Communications Library)

Advancing Recommender Systems with Graph Convolutional Networks

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