Papers with Code 아카이브
Skin Lesion Classification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 2
- 보존된 평가 기록
- 5
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Jwicaksana/FedNPR
공식 코드Non-parametric regularization for class imbalance federated medical image classification
https://github.com/Woodman718/FixCaps
공식 코드https://github.com/YeongChanLee/WonDerM_ISIC2018_SkinLesionAnalysis
공식 코드WonDerM: Skin Lesion Classification with Fine-tuned Neural Networks
https://github.com/adriano-lucieri/shape-bias-in-dermoscopy
공식 코드Revisiting the Shape-Bias of Deep Learning for Dermoscopic Skin Lesion Classification
https://github.com/alceubissoto/debiasing-skin
공식 코드https://github.com/arezou-pakzad/circle
공식 코드CIRCLe: Color Invariant Representation Learning for Unbiased Classification of Skin Lesions
https://github.com/autumn9999/mtc-with-category-shifts
공식 코드Association Graph Learning for Multi-Task Classification with Category Shifts
https://github.com/clu5/aaai22
공식 코드Fair Conformal Predictors for Applications in Medical Imaging
https://github.com/cristianopatricio/coherent-cbe-skin
공식 코드Coherent Concept-based Explanations in Medical Image and Its Application to Skin Lesion Diagnosis
https://github.com/cristianopatricio/concept-based-interpretability-vlm
공식 코드Towards Concept-based Interpretability of Skin Lesion Diagnosis using Vision-Language Models
https://github.com/devd1092/ood-skin-lesion
공식 코드Out-of-Distribution Detection for Long-tailed and Fine-grained Skin Lesion Images
https://github.com/dylan-h-wang/skin-sm3
공식 코드Self-Supervised Multi-Modality Learning for Multi-Label Skin Lesion Classification
https://github.com/enkiwang/portable-skin-lesion-diagnosis
공식 코드https://github.com/fabioperez/skin-data-augmentation
공식 코드https://github.com/felixwag/staralign
공식 코드https://github.com/hasibzunair/adversarial-lesions
공식 코드Melanoma Detection using Adversarial Training and Deep Transfer Learning
https://github.com/hazardfy/fiba
공식 코드FIBA: Frequency-Injection based Backdoor Attack in Medical Image Analysis
https://github.com/j05t/lesion-analysis
공식 코드https://github.com/jwicaksana/fca
공식 코드FCA: Taming Long-tailed Federated Medical Image Classification by Classifier Anchoring
https://github.com/learningtitans/cvpr-skin-solo-ensemble
공식 코드Solo or Ensemble? Choosing a CNN Architecture for Melanoma Classification
https://github.com/longman-stan/skindistilvit
공식 코드SkinDistilViT: Lightweight Vision Transformer for Skin Lesion Classification
https://github.com/mayurmallya/deepguide
공식 코드https://github.com/miltonbd/ISIC_2018_classification
공식 코드https://github.com/ngessert/patch-lesion
공식 코드Skin Lesion Classification Using CNNs with Patch-Based Attention and Diagnosis-Guided Loss Weighting
https://github.com/nourhanb/biaspruner
공식 코드BiasPruner: Debiased Continual Learning for Medical Image Classification
https://github.com/obsinaan/detecting-melanoma-fairly
공식 코드Detecting Melanoma Fairly: Skin Tone Detection and Debiasing for Skin Lesion Classification
https://github.com/pbevan1/detecting-melanoma-fairly
공식 코드Detecting Melanoma Fairly: Skin Tone Detection and Debiasing for Skin Lesion Classification
https://github.com/raumannsr/ENHANCE
공식 코드https://github.com/robbiemeyer/pw_loss_pruning
공식 코드https://github.com/scott-yjyang/diffmic
공식 코드DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification
https://github.com/siyi-wind/FairDisCo
공식 코드FairDisCo: Fairer AI in Dermatology via Disentanglement Contrastive Learning
https://github.com/tbdair/fedperlv1.0
공식 코드Semi-Supervised Federated Peer Learning for Skin Lesion Classification
https://github.com/theundercover01/caga-a-cascaded-dilated-convolution-approach-for-mpox-lesion-classification
공식 코드A Cascaded Dilated Convolution Approach for Mpox Lesion Classification
https://github.com/wuyxin/disc
공식 코드Discover and Cure: Concept-aware Mitigation of Spurious Correlation
https://github.com/xmed-lab/fopro-kd
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.