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Barnes and Noble

Convolutional Neural Networks for Medical Image Processing Applications

Current price: $180.00
Convolutional Neural Networks for Medical Image Processing Applications
Convolutional Neural Networks for Medical Image Processing Applications

Barnes and Noble

Convolutional Neural Networks for Medical Image Processing Applications

Current price: $180.00
Loading Inventory...

Size: Hardcover

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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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Barnes & Noble does business -- big business -- by the book. As the #1 bookseller in the US, it operates about 720 Barnes & Noble superstores (selling books, music, movies, and gifts) throughout all 50 US states and Washington, DC. The stores are typically 10,000 to 60,000 sq. ft. and stock between 60,000 and 200,000 book titles. Many of its locations contain Starbucks cafes, as well as music departments that carry more than 30,000 titles.

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