figure2 (IMAGE)
Caption
Performance validation results (confusion matrices) showing accurate classification of drone types and flight modes across various conditions: (a) 13-class flight-mode identification, (b) 7-class drone-type classification, and (c) 23-class multi-dataset extension.
Credit
D. Y. Kim, J. Kang, C. -H. Lee and W. Lim, "UAV-NAS: UAV Identification on FPGAs via Neural Architecture Search," in IEEE Transactions on Industrial Informatics, vol. 22, no. 8, pp. 7347-7358, Aug. 2026, doi: 10.1109/TII.2026.3685163. keywords: {Space exploration;Space technology;Radio broadcasting;Frequency modulation;Radio networks;Field programmable gate arrays;Central Processing Unit;System-on-chip;Integrated circuits;AI accelerators;Edge deployment;energy efficiency;field programmable gate array;neural architecture search (NAS);unmanned aerial vehicle (UAV)}
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