Search Results for author:
Found 6 papers, 5 papers with code
Search for temporal cell segmentation robustness in phase-contrast microscopy videos
Studying cell morphology changes in time is critical to understanding cell migration mechanisms.
Recovering the Imperfect: Cell Segmentation in the Presence of Dynamically Localized Proteins
In this paper, we provide a solution to segmentation of imperfect data through time based on temporal propagation and uncertainty estimation.
Parting with Illusions about Deep Active Learning
Active learning aims to reduce the high labeling cost involved in training machine learning models on large datasets by efficiently labeling only the most informative samples.
Learning Representations for Predicting Future Activities
Foreseeing the future is one of the key factors of intelligence.
Uncertainty Estimates and Multi-Hypotheses Networks for Optical Flow
Optical flow estimation can be formulated as an end-to-end supervised learning problem, which yields estimates with a superior accuracy-runtime tradeoff compared to alternative methodology.
3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
This paper introduces a network for volumetric segmentation that learns from sparsely annotated volumetric images.
Ranked #25 on
3D Instance Segmentation
on ScanNet(v2)
