1 citations · 1 across the 3 of their papers we have counts for
3 papers
Embedding Provenance in Computer Vision Datasets with JSON-LD
Lynn Vonderhaar, Timothy Elvira, Tyler Thomas Procko +1
With the ubiquity of computer vision in industry, the importance of image provenance is becoming more apparent. Provenance provides information about the origin and derivation of s…
Towards Robust Training Datasets for Machine Learning with Ontologies: A Case Study for Emergency Road Vehicle Detection
Lynn Vonderhaar, Timothy Elvira, Tyler Procko +1
Countless domains rely on Machine Learning (ML) models, including safety-critical domains, such as autonomous driving, which this paper focuses on. While the black box nature of ML…
Measuring the Impact of Scene Level Objects on Object Detection: Towards Quantitative Explanations of Detection Decisions
Lynn Vonder Haar, Timothy Elvira, Luke Newcomb +1
Although accuracy and other common metrics can provide a useful window into the performance of an object detection model, they lack a deeper view of the model's decision process. R…