Ignorance is bliss: flawed assumptions in simulated ground truth

Andrew R. Buck; Derek T. Anderson; Joshua Fraser; Jeffrey Kerley; Kannappan Palaniappan

doi:10.1117/12.2657575

13 June 2023 Ignorance is bliss: flawed assumptions in simulated ground truth

Andrew R. Buck, Derek T. Anderson, Joshua Fraser, Jeffrey Kerley, Kannappan Palaniappan

Proceedings Volume 12529, Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications; 1252905 (2023) https://doi.org/10.1117/12.2657575
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

Current generation artificial intelligence (AI) is heavily reliant on data and supervised learning (SL). However, dense and accurate truth for SL is often a bottleneck and any imperfections can negatively impact performance and/or result in biases. As a result, several corrective lines of research are being explored, including simulation (SIM). In this article, we discuss fundamental limitations in obtaining truth, both in the physical universe and SIM, and different truth uncertainty modeling strategies are explored. A case study from data-driven monocular vision is provided. These experiments demonstrate performance variability with respect to different truth uncertainty strategies in training and evaluating AI algorithms.

Conference Presentation

Citation Download Citation

Andrew R. Buck, Derek T. Anderson, Joshua Fraser, Jeffrey Kerley, and Kannappan Palaniappan "Ignorance is bliss: flawed assumptions in simulated ground truth", Proc. SPIE 12529, Synthetic Data for Artificial Intelligence and Machine Learning: Tools, Techniques, and Applications, 1252905 (13 June 2023); https://doi.org/10.1117/12.2657575

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