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cs.CV2022
Active Learning for Imbalanced Civil Infrastructure Data
Thomas Frick, Diego Antognini, Mattia Rigotti +3
Aging civil infrastructures are closely monitored by engineers for damage and critical defects. As the manual inspection of such large structures is costly and time-consuming, we a…
cs.CV2022
Model-Assisted Labeling via Explainability for Visual Inspection of Civil Infrastructures
Klara Janouskova, Mattia Rigotti, Ioana Giurgiu +1
Labeling images for visual segmentation is a time-consuming task which can be costly, particularly in application domains where labels have to be provided by specialized expert ann…
cs.LG2022
Enabling Reproducibility and Meta-learning Through a Lifelong Database of Experiments (LDE)
Jason Tsay, Andrea Bartezzaghi, Aleke Nolte +1
Artificial Intelligence (AI) development is inherently iterative and experimental. Over the course of normal development, especially with the advent of automated AI, hundreds or th…