Adaptive Context Selection for Polyp Segmentation
Authors:
Top Cited Papers
- 29 September 2020
- book chapter
- Published by Springer Nature
- p. 253-262
Abstract
No abstract availableKeywords
All Related Versions
This publication has 18 references indexed in Scilit:
- Kvasir-SEG: A Segmented Polyp Dataset2019
- Selective Feature Aggregation Network with Area-Boundary Constraints for Polyp Segmentation2019
- Adaptive Context Network for Scene Parsing2019
- Non-Local Context Encoder: Robust Biomedical Image Segmentation against Adversarial AttacksProceedings of the AAAI Conference on Artificial Intelligence, 2019
- Polyp Segmentation in Colonoscopy Images Using Fully Convolutional Network2018
- Squeeze-and-Excitation Networks2018
- Contrast-Oriented Deep Neural Networks for Salient Object DetectionIEEE Transactions on Neural Networks and Learning Systems, 2018
- Feature Pyramid Networks for Object Detection2017
- Fully convolutional neural networks for polyp segmentation in colonoscopy2017
- Deep Residual Learning for Image Recognition2016