Aug 18, 2019 · An effective way to solve it is to increase the number of minority class samples in the dataset. Many methods are put forward to solve the ...
Aug 19, 2019 · And finally the classification networks for skin lesions are trained by data collaboration which consist of real images and generated images.
An effective way to solve it is to increase the number of minority class samples in the dataset. Many methods are put forward to solve the problem of imbalance ...
An effective way to solve it is to increase the number of minority class samples in the dataset. Many methods are put forward to solve the problem of imbalance ...
Oct 4, 2022 · The skin classification approaches can be divided into two main approaches: Deep Learning and Machine Learning (as shown in Table 1). Both ...
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MobileSkin: Classification of Skin Lesion Images Acquired Using ...
www.ncbi.nlm.nih.gov › PMC9457478
Aug 30, 2022 · This study presents a dataset consisting of dermoscopic images taken using a mobile phone-attached hand-held dermoscope.
We propose data balanced methods to solve this data imbalanced problem, including data augmentation, data balancing, and the multi-model ensemble.
Jun 19, 2023 · The authors proposed a new Artificial Intelligence-Based method to classify skin lesions. In this method, we used Residual Deep Convolution Neural Network.
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This research introduces a skin lesion classification system that harnesses the capabilities of three advanced deep learning models: VGG16, Inception-V3, and ...
Nov 15, 2023 · This research uses a hybrid deep learning model that combines two cutting-edge approaches: Mask Region-based Convolutional Neural Network (MRCNN) ...