9 citations · 23 across the 8 of their papers we have counts for
8 papers
DELINE8K: A Synthetic Data Pipeline for the Semantic Segmentation of Historical Documents
Taylor Archibald, Tony Martinez
Document semantic segmentation is a promising avenue that can facilitate document analysis tasks, including optical character recognition (OCR), form classification, and document e…
Generalizing Interactive Backpropagating Refinement for Dense Prediction
Fanqing Lin, Brian Price, Tony Martinez
As deep neural networks become the state-of-the-art approach in the field of computer vision for dense prediction tasks, many methods have been developed for automatic estimation o…
A Hierarchical Multi-Output Nearest Neighbor Model for Multi-Output Dependence Learning
Richard G. Morris, Tony Martinez, Michael R. Smith
Multi-Output Dependence (MOD) learning is a generalization of standard classification problems that allows for multiple outputs that are dependent on each other. A primary issue th…
Recommending Learning Algorithms and Their Associated Hyperparameters
Michael R. Smith, Logan Mitchell, Christophe Giraud-Carrier +1
The success of machine learning on a given task dependson, among other things, which learning algorithm is selected and its associated hyperparameters. Selecting an appropriate lea…
An Easy to Use Repository for Comparing and Improving Machine Learning Algorithm Usage
Michael R. Smith, Andrew White, Christophe Giraud-Carrier +1
The results from most machine learning experiments are used for a specific purpose and then discarded. This results in a significant loss of information and requires rerunning expe…
Reducing the Effects of Detrimental Instances
Michael R. Smith, Tony Martinez
Not all instances in a data set are equally beneficial for inducing a model of the data. Some instances (such as outliers or noise) can be detrimental. However, at least initially,…