An architecture for tactical intention recognition of aerial targets based on unsupervised momentum contrast and transformer

Abstract Tactical intention recognition of aerial targets is critical for battlefield decision-making, yet existing supervised deep learning approaches face fundamental challenges due to the extreme scarcity of labeled training data in military domains, where data annotation is constrained by securi...

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Bibliografische Detailangaben

Hauptverfasser:	Yafei Song, Lemin Li, Wen Quan, Peng Ni, Wen Sun, Ke Wang, TianPeng Li
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	SpringerOpen 2026-03-01
Schriftenreihe:	Journal of Big Data
Schlagworte:	Intention recognition Momentum contrast learning K-NN Transformer
Online-Zugang:	https://doi.org/10.1186/s40537-026-01403-x
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