Document Type
Article
Publication Date
11-19-2024
Abstract
Excerpt: Increasing reliance on autonomous systems requires confidence in the accuracies produced from computer vision classification algorithms. Computer vision (CV) for video classification provides phenomenal abilities, but it often suffers from “flickering” of results. Flickering occurs when the CV algorithm switches between declared classes over successive frames. Such behavior causes a loss of trust and confidence in their operations.
Source Publication
Journal of Defense Analytics and Logistics (e-ISSN 2399-6439)
Recommended Citation
Miller, N., Drumm, G. R., Champagne, L., Cox, B., & Bihl, T. (2024). Strategies to alleviate flickering: Bayesian and smoothing methods for deep learning classification in video. Journal of Defense Analytics and Logistics. https://doi.org/10.1108/JDAL-09-2023-0010
Included in
Computer Sciences Commons, Other Operations Research, Systems Engineering and Industrial Engineering Commons, Signal Processing Commons
Comments
Copyright © 2024, Noah Miller, Glen Ryan Drumm, Lance Champagne, Bruce Cox and Trevor Bihl
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