Convolutional Neural Networks for Medical Image Processing Applications (eBook, ePUB)
Redaktion: Ozturk, Saban
55,95 €
55,95 €
inkl. MwSt.
Sofort per Download lieferbar
28 °P sammeln
55,95 €
Als Download kaufen
55,95 €
inkl. MwSt.
Sofort per Download lieferbar
28 °P sammeln
Jetzt verschenken
Alle Infos zum eBook verschenken
55,95 €
inkl. MwSt.
Sofort per Download lieferbar
Alle Infos zum eBook verschenken
28 °P sammeln
Convolutional Neural Networks for Medical Image Processing Applications (eBook, ePUB)
Redaktion: Ozturk, Saban
- Format: ePub
- Merkliste
- Auf die Merkliste
- Bewerten Bewerten
- Teilen
- Produkt teilen
- Produkterinnerung
- Produkterinnerung

Bitte loggen Sie sich zunächst in Ihr Kundenkonto ein oder registrieren Sie sich bei
bücher.de, um das eBook-Abo tolino select nutzen zu können.
Hier können Sie sich einloggen
Hier können Sie sich einloggen
Sie sind bereits eingeloggt. Klicken Sie auf 2. tolino select Abo, um fortzufahren.

Bitte loggen Sie sich zunächst in Ihr Kundenkonto ein oder registrieren Sie sich bei bücher.de, um das eBook-Abo tolino select nutzen zu können.
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.
- Geräte: eReader
- ohne Kopierschutz
- eBook Hilfe
- Größe: 17.23MB
Andere Kunden interessierten sich auch für
- Convolutional Neural Networks for Medical Image Processing Applications (eBook, PDF)55,95 €
- Recent Advances in AI-enabled Automated Medical Diagnosis (eBook, ePUB)53,95 €
- Mitul Kumar AhirwalArtificial Intelligence Applications for Health Care (eBook, ePUB)47,95 €
- Artificial Intelligence Technologies for Computational Biology (eBook, ePUB)48,95 €
- Yongjie Jessica ZhangGeometric Modeling and Mesh Generation from Scanned Images (eBook, ePUB)50,95 €
- Vassilka Tabakovae-Learning in Medical Physics and Engineering (eBook, ePUB)48,95 €
- Combating Women's Health Issues with Machine Learning (eBook, ePUB)52,95 €
-
-
-
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.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis eBooks
- Seitenzahl: 274
- Erscheinungstermin: 23. Dezember 2022
- Englisch
- ISBN-13: 9781000818055
- Artikelnr.: 66360338
- Verlag: Taylor & Francis eBooks
- Seitenzahl: 274
- Erscheinungstermin: 23. Dezember 2022
- Englisch
- ISBN-13: 9781000818055
- Artikelnr.: 66360338
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
¿aban Öztürk is an Associate Professor in Amasya University, Amasya, Turkey. He obtained his B.S., M.S. Ph.D. in Electrical and Electronics Engineering from Selçuk University, Turkey in 2011, 2015, and 2019, respectively. He lectures in artificial intelligence and image processing related courses at the Amasya University. Also, he is the head of the Visual Understanding in Biomedical Images laboratory. His research interests encompass artificial intelligence, medical image analysis and deep learning applications. He has more than 50 published articles and proceedings.
Convolutional neural networks for segmentation in short-axis cine cardiac magnetic resonance imaging: review and considerations. Comparison of Traditional Machine Learning Algorithms and Convolution Neural Networks for Detection of Peripheral Malarial Parasites in Blood Smears. Deep Learning-Based Computer-Aided Diagnosis System for Attention Deficit Hyperactivity Disorder Classification Using Synthetic Data. Basic Ensembles of Vanilla-Style Deep Learning Models Improve Liver Segmentation from CT Images. Convolutional Neural Networks for Medical Image Analysis. Ulcer and Red Lesion Detection in Wireless Capsule Endoscopy Images using CNN. Do More with Less: Deep Learning in Medical Imaging. Automatic Classification of fMRI Signals from Behavioral, Cognitive and Affective Tasks Using Deep Learning. Detection of COVID-19 in Lung CT-Scans using Reconstructed Image Features. Dental image analysis: Where deep learning meets dentistry. Malarial Parasite Detection in Blood Smear Microscopic Images: A Review on Deep Learning Approaches. Automatic Classification of Coronary Stenos is using Convolutional Neural Networks and Simulated Annealing. Deep Learning Approach for Detecting COVID-19 from Chest X-ray Images.
Convolutional neural networks for segmentation in short-axis cine cardiac magnetic resonance imaging: review and considerations. Comparison of Traditional Machine Learning Algorithms and Convolution Neural Networks for Detection of Peripheral Malarial Parasites in Blood Smears. Deep Learning-Based Computer-Aided Diagnosis System for Attention Deficit Hyperactivity Disorder Classification Using Synthetic Data. Basic Ensembles of Vanilla-Style Deep Learning Models Improve Liver Segmentation from CT Images. Convolutional Neural Networks for Medical Image Analysis. Ulcer and Red Lesion Detection in Wireless Capsule Endoscopy Images using CNN. Do More with Less: Deep Learning in Medical Imaging. Automatic Classification of fMRI Signals from Behavioral, Cognitive and Affective Tasks Using Deep Learning. Detection of COVID-19 in Lung CT-Scans using Reconstructed Image Features. Dental image analysis: Where deep learning meets dentistry. Malarial Parasite Detection in Blood Smear Microscopic Images: A Review on Deep Learning Approaches. Automatic Classification of Coronary Stenos is using Convolutional Neural Networks and Simulated Annealing. Deep Learning Approach for Detecting COVID-19 from Chest X-ray Images.