Skin Cancer Classification

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

15 shown of 15 papers with code (45 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Skin Lesion Synthesis with Generative Adversarial Networks
  8 Feb 2019 2 repositories listed
  Skin cancer is by far the most common type of cancer.
• Knowledge Transfer for Melanoma Screening with Deep Learning
  22 Mar 2017 2 repositories listed
  Knowledge transfer impacts the performance of deep learning -- the state of the art for image classification tasks, including automated melanoma screening.
• Cancer-Net SCa-Synth: An Open Access Synthetically Generated 2D Skin Lesion Dataset for Skin Cancer Classification
  8 Nov 2024 1 repository listed
  In healthcare, generative artificial intelligence (AI) models have been employed to create synthetic data, addressing data imbalance in datasets by augmenting underrepresented classes and enhancing the overall quality…
• A Wavelet Guided Attention Module for Skin Cancer Classification with Gradient-based Feature Fusion
  21 Jun 2024 1 repository listed
  In this paper, we propose a novel model, which uses a novel attention mechanism to pinpoint the differences in features across the spatial dimensions and symmetry of the lesion, thereby focusing on the dissimilarities…
• Revisiting Skin Tone Fairness in Dermatological Lesion Classification
  18 Aug 2023 1 repository listed
  Addressing fairness in lesion classification from dermatological images is crucial due to variations in how skin diseases manifest across skin tones.
• SkinDistilViT: Lightweight Vision Transformer for Skin Lesion Classification
  16 Aug 2023 1 repository listed
  By adding classification heads at each level of the transformer and employing a cascading distillation process, we improve the balanced multi-class accuracy of the base model by 2.
• Skin Deep Unlearning: Artefact and Instrument Debiasing in the Context of Melanoma Classification
  20 Sep 2021 1 repository listed Syntology ran 4 of 5 samples · 1 unverified
  Convolutional Neural Networks have demonstrated dermatologist-level performance in the classification of melanoma from skin lesion images, but prediction irregularities due to biases seen within the training data are an…
• Soft-Attention Improves Skin Cancer Classification Performance
  5 May 2021 1 repository listed
  Soft-Attention mechanism enables a neural network toachieve this goal.
• Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training
  30 Mar 2021 1 repository listed
  Data augmentation has proved extremely useful by increasing training data variance to alleviate overfitting and improve deep neural networks' generalization performance.
• Semi-Supervised Federated Peer Learning for Skin Lesion Classification
  5 Mar 2021 1 repository listed
  With few annotated data, FedPerl is on par with a state-of-the-art method in skin lesion classification in the standard setup while outperforming SSFLs and the baselines by 1.
• Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
  15 Aug 2020 1 repository listed Syntology ran 1 of 24 samples · 23 unverified
  Particularly concerning are models with inconsistent performance on specific subgroups of a class, e.
• Melanoma Detection using Adversarial Training and Deep Transfer Learning
  14 Apr 2020 1 repository listed
  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…
• Deep neural network or dermatologist?
  19 Aug 2019 1 repository listed
  We show that despite high accuracy, the models will occasionally assign importance to features that are not relevant to the diagnostic task.
• Skin Cancer Segmentation and Classification with NABLA-N and Inception Recurrent Residual Convolutional Networks
  25 Apr 2019 1 repository listed
  Several DL architectures have been proposed for classification, segmentation, and detection tasks in medical imaging and computational pathology.
• Data Augmentation for Skin Lesion Analysis
  5 Sep 2018 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  In this work, we investigate the impact of 13 data augmentation scenarios for melanoma classification trained on three CNNs (Inception-v4, ResNet, and DenseNet).

Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.