Dr. Sara Wheeland Profile

Dr. Sara Wheeland

at Naval Information Warfare Ctr Pacific

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Proceedings Article | 9 May 2024 Poster + Paper

Single image wire corrosion level identification using explainable AI

Shibin Parameswaran, Sara Wheeland, Ivan Febus-Rivera

Proceedings Volume 12950, 129500U (2024) https://doi.org/10.1117/12.3027476

KEYWORDS: Corrosion, Image processing, Deep learning, Artificial intelligence, Computer vision technology

Read Abstract +

Guy wires stabilize outdoor structures typically up to hundreds of feet in height. Exposed to potentially harsh environmental conditions, these wires can experience internal and external corrosion. Up-close visual inspection is often unrealistic given the height. A typical way to characterize corrosion involves taking samples of the wire, which requires destruction and replacement of the current wire. Non-destructive methods are preferred for this reason. To this end, we explore the feasibility of using computer vision techniques on images captured from Unmanned Aerial Vehicles (UAV) to automatically detect corrosion or swelling due to internal corrosion on a wire or cable. We leverage a data-centric approach to train a classifier for identifying corrosion level from a single RGB image. We evaluate the model performance on a dataset of wire images displaying 4 different corrosion levels. Finally, in order to provide additional insights and explainability to a human operator, we use GradCam to analyze the model's decision-making process and identify parts of an image that contributed to the resulting corrosion level label.

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