Classification of Skin Lesion using Image Processing : Machine Learning, Deep Learning, Ensemble Learning and Shallow Neural Network.DE
Language: English
Published by LAP Lambert Academic Publishing, 2023
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 59.04
Quantity: 2 available
Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - Skin Cancer is the most dangerous type of cancer. The early detection and action can severely reduce the death rate. The advanced technology like machine learning and deep learning makes the possibility of identifying the accurate type of skin disease. The book covers the concept of artificial intelligence, machine learning, deep learning, ensemble learning and shallow neural network in analysis of skin lesion. It also talks about the computer aided diagnostic system in which complete phases from image acquisition, preprocessing, feature extraction, feature reduction and classification through various algorithms is showcased. The database plays a vital role in accurate classification. In this, we have considered the standard dataset for seven types of skin diseases from International Skin Imaging Collaboration(ISIC). The role of DEnSha(Deep, Ensemble and Shallow neural network) is elaborated for early detection and classification of skin disease keeping the performance measures in consideration.…
Seller Inventory # 9786206162995
- Title
- Classification of Skin Lesion using Image Processing : Machine Learning, Deep Learning, Ensemble Learning and Shallow Neural Network.DE
- Author
- Ginni Arora
- Publisher
- LAP Lambert Academic Publishing
- Publication year
- 2023
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 6206162990
- ISBN 13
- 9786206162995
- Dimensions
- 220x150x33 mm
"Synopsis" may belong to another edition of this title.
Shipping rates from Germany to U.S.A.
| Item | 7 to 10 business days | 5 to 7 business days |
|---|---|---|
| First item | £ 29.31 | £ 37.69 |
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