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Augmenting data with GANs to segment melanoma skin lesions

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Augmenting data with GANs to segment melanoma skin lesions

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Pollastri, F.; Bolelli, F.; Paredes Palacios, R.; Grana, C. (2020). Augmenting data with GANs to segment melanoma skin lesions. Multimedia Tools and Applications. 79(21-22):15575-15592. https://doi.org/10.1007/s11042-019-7717-y

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/168114

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Title: Augmenting data with GANs to segment melanoma skin lesions
Author: Pollastri, Federico Bolelli, Federico Paredes Palacios, Roberto Grana, Costantino
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Issued date:
Abstract:
[EN] This paper presents a novel strategy that employs Generative Adversarial Networks (GANs) to augment data in the skin lesion segmentation task, which is a fundamental first step in the automated melanoma detection ...[+]
Subjects: Deep learning , Convolutional neural networks , Adversarial learning , Skin lesion segmentation
Copyrigths: Cerrado
Source:
Multimedia Tools and Applications. (issn: 1380-7501 )
DOI: 10.1007/s11042-019-7717-y
Publisher:
Springer-Verlag
Publisher version: https://doi.org/10.1007/s11042-019-7717-y
Type: Artículo

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