Papers with Code 아카이브
Retinal OCT Disease Classification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Classifying different Retinal degeneration from Optical Coherence Tomography Images (OCT).
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
TINC: Temporally Informed Non-Contrastive Learning for Disease Progression Modeling in Retinal OCT Volumes
Demystifying Deep Learning Models for Retinal OCT Disease Classification using Explainable AI
Matching the Clinical Reality: Accurate OCT-Based Diagnosis From Few Labels
Improving Robustness using Joint Attention Network For Detecting Retinal Degeneration From Optical Coherence Tomography Images
Optic-Net: A Novel Convolutional Neural Network for Diagnosis of Retinal Diseases from Optical Tomography Images
Retinal OCT disease classification with variational autoencoder regularization
MobileNetV2: Inverted Residuals and Linear Bottlenecks
Deep learning is effective for the classification of OCT images of normal versus Age-related Macular Degeneration
Deep Residual Learning for Image Recognition
Rethinking the Inception Architecture for Computer Vision
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.