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12 April 2021 What’s data got to do with it?
Jamie Godwin, Donald Waagen, Donald Hulsey, Ryland Lyons, Rachel Mattson, Jacob Garcia, Duane Geci, Railey Conner
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Proceedings Volume 11746, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III; 117460Q (2021) https://doi.org/10.1117/12.2587479
Event: SPIE Defense + Commercial Sensing, 2021, Online Only
Abstract
Continued advancements in adversarial attacks have crippled neural network performance. These small pixel perturbations can go undetected and cause networks to misclassify with high confidence. The motivation for this paper was to investigate how various sensor modalities and network models respond to adversarial attacks. It is important to realize that the large diversity in neural network architectures makes it difficult for any analytical conclusions to be made that generalize across any given neural network. For this reason, we share the statistical analyses performed which could be applied to any network under review. General observations gained from this analysis are also shared which indicated that network classification accuracy is not just a function of the network model but the data as well.
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Jamie Godwin, Donald Waagen, Donald Hulsey, Ryland Lyons, Rachel Mattson, Jacob Garcia, Duane Geci, and Railey Conner "What’s data got to do with it?", Proc. SPIE 11746, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III, 117460Q (12 April 2021); https://doi.org/10.1117/12.2587479
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KEYWORDS
Data modeling
Statistical analysis
Distance measurement
Neural networks
Analytical research
Network architectures
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