Classification of Skin Lesion using Image Processing : Machine Learning, Deep Learning, Ensemble Learning and Shallow Neural Network.DE

Ginni Arora

ISBN 10: 6206162990 / ISBN 13: 9786206162995

Editore: LAP Lambert Academic Publishing, 2023

Riguardo questo articolo

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.

Codice articolo 9786206162995

Dati bibliografici

• Titolo: Classification of Skin Lesion using Image Processing : Machine Learning, Deep Learning, Ensemble Learning and Shallow Neural Network.DE
• Editore: LAP Lambert Academic Publishing
• Data di pubblicazione: 2023
• Lingua: Inglese
• ISBN 10: 6206162990
• ISBN 13: 9786206162995
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 220 L x 150 A x 33 P (millimetri) 220 millimetri di larghezza per 150 millimetri di altezza per 33 millimetri di profondità

Descrizione articolo

Riassunto

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.