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Found 6 papers, 2 papers with code
FISBe: A Real-World Benchmark Dataset for Instance Segmentation of Long-Range Thin Filamentous Structures
Lastly we provide three baselines to kick off a competition that we envision to both advance the field of machine learning regarding methodology for capturing long-range data dependencies and facilitate scientific discovery in basic neuroscience.
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting
Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome.
Panoptic segmentation with highly imbalanced semantic labels
We describe here the panoptic segmentation method we devised for our participation in the CoNIC: Colon Nuclei Identification and Counting Challenge at ISBI 2022.
How Shift Equivariance Impacts Metric Learning for Instance Segmentation
In our work, we contribute a comprehensive formal analysis of the shift equivariance properties of encoder-decoder-style CNNs, which yields a clear picture of what can and cannot be achieved with metric learning in the face of same-looking objects.
Probabilistic Deep Learning for Instance Segmentation
Probabilistic convolutional neural networks, which predict distributions of predictions instead of point estimates, led to recent advances in many areas of computer vision, from image reconstruction to semantic segmentation.
State of the Art in Fair ML: From Moral Philosophy and Legislation to Fair Classifiers
Machine learning is becoming an ever present part in our lives as many decisions, e. g. to lend a credit, are no longer made by humans but by machine learning algorithms.
