Skin Lesion Classification Using Deep Neural Network

11/18/2019 ∙ by Alla Eddine Guissous, et al. ∙ 0 ∙ share

This paper reports the methods and techniques we have developed for classify dermoscopic images (task 1) of the ISIC 2019 challenge dataset for skin lesion classification, our approach aims to use ensemble deep neural network with some powerful techniques to deal with unbalance data sets as its the main problem for this challenge in a move to increase the performance of CNNs model.

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Skin Lesion Classification Using Deep Neural Network

Authors

Skin disease identification from dermoscopy images using deep convolutional neural network

Skin Lesion Classification Using Deep Multi-scale Convolutional Neural Networks

Image Classification of Melanoma, Nevus and Seborrheic Keratosis by Deep Neural Network Ensemble

Deep neural network ensemble by data augmentation and bagging for skin lesion classification

Skin Lesion Classification Using Ensembles of Multi-Resolution EfficientNets with Meta Data

Horizontal and Vertical Ensemble with Deep Representation for Classification

Disease Classification within Dermascopic Images Using features extracted by ResNet50 and classification through Deep Forest

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