Abstract
This disclosure presents a novel approach to processing and analyzing satellite data cubes using a Nautilus Spiking Neural Network (SNN) architecture combined with analog-inspired preprocessing techniques. This method significantly reduces data payload size while maintaining information integrity, enabling more efficient storage, transmission, and analysis of multi-spectral, multi-temporal satellite imagery.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Gagnon, Renee, "Nautilus Spiking Neural Network for Efficient Satellite Data Cube Analysis", Technical Disclosure Commons, (July 16, 2024)
https://www.tdcommons.org/dpubs_series/7198
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