291 citations · 292 across the 5 of their papers we have counts for
5 papers
Metadata Improves Segmentation Through Multitasking Elicitation
Iaroslav Plutenko, Mikhail Papkov, Kaupo Palo +2
Metainformation is a common companion to biomedical images. However, this potentially powerful additional source of signal from image acquisition has had limited use in deep learni…
Developing a data analysis pipeline for automated protein profiling in immunology
Dmytro Fishman
Accurate information about protein content in the organism is instrumental for a better understanding of human biology and disease mechanisms. While the presence of certain types o…
Noise2Stack: Improving Image Restoration by Learning from Volumetric Data
Mikhail Papkov, Kenny Roberts, Lee Ann Madissoon +4
Biomedical images are noisy. The imaging equipment itself has physical limitations, and the consequent experimental trade-offs between signal-to-noise ratio, acquisition speed, and…
DOME: Recommendations for supervised machine learning validation in biology
Ian Walsh, Dmytro Fishman, Dario Garcia-Gasulla +6
Modern biology frequently relies on machine learning to provide predictions and improve decision processes. There have been recent calls for more scrutiny on machine learning perfo…
A Survey of End-to-End Driving: Architectures and Training Methods
Ardi Tampuu, Maksym Semikin, Naveed Muhammad +2
Autonomous driving is of great interest to industry and academia alike. The use of machine learning approaches for autonomous driving has long been studied, but mostly in the conte…