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Greatest papers with code

Knowledge Transfer for Melanoma Screening with Deep Learning

22 Mar 2017learningtitans/isbi2017-part3

Knowledge transfer impacts the performance of deep learning -- the state of the art for image classification tasks, including automated melanoma screening.

IMAGE CLASSIFICATION SKIN CANCER CLASSIFICATION TRANSFER LEARNING

Data Augmentation for Skin Lesion Analysis

5 Sep 2018fabioperez/skin-data-augmentation

In this work, we investigate the impact of 13 data augmentation scenarios for melanoma classification trained on three CNNs (Inception-v4, ResNet, and DenseNet).

DATA AUGMENTATION SKIN CANCER CLASSIFICATION SKIN LESION CLASSIFICATION

Model Patching: Closing the Subgroup Performance Gap with Data Augmentation

ICLR 2021 HazyResearch/model-patching

Particularly concerning are models with inconsistent performance on specific subgroups of a class, e. g., exhibiting disparities in skin cancer classification in the presence or absence of a spurious bandage.

DATA AUGMENTATION SKIN CANCER CLASSIFICATION

Melanoma Detection using Adversarial Training and Deep Transfer Learning

Journal of Physics in Medicine and Biology 2020 hasibzunair/adversarial-lesions

In the first stage, we leverage the inter-class variation of the data distribution for the task of conditional image synthesis by learning the inter-class mapping and synthesizing under-represented class samples from the over-represented ones using unpaired image-to-image translation.

CONDITIONAL IMAGE GENERATION IMAGE-TO-IMAGE TRANSLATION LESION CLASSIFICATION MEDICAL IMAGE GENERATION SKIN CANCER CLASSIFICATION SKIN LESION CLASSIFICATION TRANSFER LEARNING

Deep neural network or dermatologist?

19 Aug 2019KyleYoung1997/DNNorDermatologist

We show that despite high accuracy, the models will occasionally assign importance to features that are not relevant to the diagnostic task.

SKIN CANCER CLASSIFICATION

Convolutional Neural Networks for Classifying Melanoma Images

14 May 2020abhinavsagar/skin-cancer

In this work, we address the problem of skin cancer classification using convolutional neural networks.

SKIN CANCER CLASSIFICATION TRANSFER LEARNING

Dermatologist Level Dermoscopy Skin Cancer Classification Using Different Deep Learning Convolutional Neural Networks Algorithms

21 Oct 2018briansukhnandan/Skin-Lesion-Classifier-CNN

The best ROC AUC values for melanoma and basal cell carcinoma are 94. 40% (ResNet 152) and 99. 30% (DenseNet 201) versus 82. 26% and 88. 82% of dermatologists, respectively.

SKIN CANCER CLASSIFICATION