Maximizing training efficiency through intelligent data exposure

Arthur C. Depoian II; Colleen P. Bailey; Parthasarathy Guturu

doi:10.1117/12.3013967

10 June 2024 Maximizing training efficiency through intelligent data exposure

Arthur C. Depoian II, Colleen P. Bailey, Parthasarathy Guturu

Proceedings Volume 13036, Big Data VI: Learning, Analytics, and Applications; 130360G (2024) https://doi.org/10.1117/12.3013967
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

Edge computing in remote sensing often necessitates on-device learning due to bandwidth and latency constraints. However, limited memory and computational power on edge devices pose challenges for traditional machine learning approaches with large datasets and complex models. Continuous learning offers a potential solution for these scenarios by enabling models to adapt to evolving data streams. This paper explores the concept of leveraging a strategically selected subset of archival training data to improve performance in continual learning. We introduce a feedback-based intelligent data sampling method that utilizes a log-normal distribution to prioritize informative data points from the original training set, focusing on samples which the model struggled with during initial training. This simulation-based exploration investigates the trade-off between accuracy gains and resource utilization with different data inclusion rates, paving the way for the deployment of this approach in real-world edge devices. This approach can lead to better decision making in the field, improved operational efficiency through reduced reliance on cloud resources, and greater system autonomy for remotely sensing tasks. This will lead to the development of robust and efficient edge-based learning systems that enable real-time, autonomous, and data-driven decisions for critical tasks in remote locations.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Arthur C. Depoian II, Colleen P. Bailey, and Parthasarathy Guturu "Maximizing training efficiency through intelligent data exposure", Proc. SPIE 13036, Big Data VI: Learning, Analytics, and Applications, 130360G (10 June 2024); https://doi.org/10.1117/12.3013967

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