Search Results for author:
Found 6 papers, 1 papers with code
COIN: Counterfactual inpainting for weakly supervised semantic segmentation for medical images
This evidence suggests that COIN is a promising approach for semantic segmentation of tumors in CT images, and presents a step forward in making deep learning applications more accessible and effective in healthcare, where annotated data is scarce.
A Survey of End-to-End Driving: Architectures and Training Methods
Autonomous driving is of great interest to industry and academia alike.
DOME: Recommendations for supervised machine learning validation in biology
Modern biology frequently relies on machine learning to provide predictions and improve decision processes.
Noise2Stack: Improving Image Restoration by Learning from Volumetric Data
As a part of this work, we release a microscopy dataset to establish a benchmark for the multiplane image denoising.
Developing a data analysis pipeline for automated protein profiling in immunology
The work that laid the foundation of this thesis has been instrumental for a number of subsequent studies of human disease and also inspired a contribution to refining standards for validation of machine learning methods in biology.
Metadata Improves Segmentation Through Multitasking Elicitation
Metainformation is a common companion to biomedical images.
