Papers with Code 아카이브
Polyp Segmentation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 2
- 보존된 평가 기록
- 10
The goal of the project is to develop a computer-aided detection and diagnosis system for automatic polyp segmentation and detection.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
KDAS: Knowledge Distillation via Attention Supervision Framework for Polyp Segmentation
TransNetR: Transformer-based Residual Network for Polyp Segmentation with Multi-Center Out-of-Distribution Testing
Multi Kernel Positional Embedding ConvNeXt for Polyp Segmentation
PatchRefineNet: Improving Binary Segmentation by Incorporating Signals from Optimal Patch-wise Binarization
TGANet: Text-guided attention for improved polyp segmentation
BDG-Net: Boundary Distribution Guided Network for Accurate Polyp Segmentation
ResUNet++: An Advanced Architecture for Medical Image Segmentation
Kvasir-SEG: A Segmented Polyp Dataset
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.