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Deep Learning for Medical Image Analysis

Engelsk Paperback

Deep Learning for Medical Image Analysis

Engelsk Paperback
Tjek vores konkurrenters priser
Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for academic and industry researchers and graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Deep learning provides exciting solutions for medical image analysis problems and is a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component are applied to medical image detection, segmentation, registration, and computer-aided analysis.
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20 kr
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God 4 anmeldelser på
Tjek vores konkurrenters priser
Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for academic and industry researchers and graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Deep learning provides exciting solutions for medical image analysis problems and is a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component are applied to medical image detection, segmentation, registration, and computer-aided analysis.
Produktdetaljer
Sprog: Engelsk
Sider: 518
ISBN-13: 9780323851244
Indbinding: Paperback
Udgave: 2
ISBN-10: 032385124X
Kategori: Machine learning
Udg. Dato: 27 nov 2023
Længde: 30mm
Bredde: 239mm
Højde: 191mm
Forlag: Elsevier Science & Technology
Oplagsdato: 27 nov 2023
Forfatter(e):
Forfatter(e)


Kategori Machine learning


ISBN-13 9780323851244


Sprog Engelsk


Indbinding Paperback


Sider 518


Udgave 2


Længde 30mm


Bredde 239mm


Højde 191mm


Udg. Dato 27 nov 2023


Oplagsdato 27 nov 2023


Forlag Elsevier Science & Technology

Kategori sammenhænge