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Found 7 papers, 7 papers with code
Enhancing Visually-Rich Document Understanding via Layout Structure Modeling
In this paper, we propose GraphLayoutLM, a novel document understanding model that leverages the modeling of layout structure graph to inject document layout knowledge into the model.
Domain Randomization-Enhanced Depth Simulation and Restoration for Perceiving and Grasping Specular and Transparent Objects
Commercial depth sensors usually generate noisy and missing depths, especially on specular and transparent objects, which poses critical issues to downstream depth or point cloud-based tasks.
Discovering Clinically Meaningful Shape Features for the Analysis of Tumor Pathology Images
With the advanced imaging technology, digital pathology imaging of tumor tissue slides is becoming a routine clinical procedure for cancer diagnosis.
Using Persistent Homology Topological Features to Characterize Medical Images: Case Studies on Lung and Brain Cancers
Tumor shape is a key factor that affects tumor growth and metastasis.
Bayesian Modeling of Microbiome Data for Differential Abundance Analysis
To overcome these challenges, we propose a Bayesian hierarchical modeling framework for the analysis of microbiome count data for differential abundance analysis.
Methodology
A Bayesian Zero-Inflated Negative Binomial Regression Model for the Integrative Analysis of Microbiome Data
Hence, we present an integrative Bayesian zero-inflated negative binomial regression model that can both distinguish differential abundant taxa with distinct phenotypes and quantify covariate-taxa effects.
Applications
A Bayesian Mark Interaction Model for Analysis of Tumor Pathology Images
This statistical methodology not only presents a new model for characterizing spatial correlations in a multi-type spatial point pattern, but also provides a new perspective for understanding the role of cell-cell interactions in cancer progression.
Methodology 62M30, 62F15
