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Found 7 papers, 4 papers with code
Revealing Cortical Layers In Histological Brain Images With Self-Supervised Graph Convolutional Networks Applied To Cell-Graphs
Identifying cerebral cortex layers is crucial for comparative studies of the cytoarchitecture aiming at providing insights into the relations between brain structure and function across species.
NCIS: Deep Color Gradient Maps Regression and Three-Class Pixel Classification for Enhanced Neuronal Cell Instance Segmentation in Nissl-Stained Histological Images
Deep learning has proven to be more effective than other methods in medical image analysis, including the seemingly simple but challenging task of segmenting individual cells, an essential step for many biological studies.
MR-NOM: Multi-scale Resolution of Neuronal cells in Nissl-stained histological slices via deliberate Over-segmentation and Merging
In comparative neuroanatomy, the characterization of brain cytoarchitecture is critical to a better understanding of brain structure and function, as it helps to distill information on the development, evolution, and distinctive features of different populations.
Advances in Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider
Between the years 2015 and 2019, members of the Horizon 2020-funded Innovative Training Network named "AMVA4NewPhysics" studied the customization and application of advanced multivariate analysis methods and statistical learning tools to high-energy physics problems, as well as developed entirely new ones.
Permutation-Based True Discovery Guarantee by Sum Tests
We present an iterative shortcut for the closed testing procedure, based on the branch and bound algorithm, which converges to the full closed testing results, often after few iterations; even if it is stopped early, it controls the TDP.
Methodology
Enhancing statistical inference in psychological research via prospective and retrospective design analysis
In the past two decades, psychological science has experienced an unprecedented replicability crisis which uncovered several issues.
Methodology Applications 62P15, 62-07, 62F03
Robust testing in generalized linear models by sign-flipping score contributions
Our test is often robust against the mentioned forms of misspecification and provides better type-I error control than its competitors.
Methodology 62G10
