Author

G. Slabaugh

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Open access Sep 2026

Low-complexity pedestrian intent prediction using contextual stacked ensemble learning

This work proposes CSE, a lightweight contextual stacked ensemble-learning framework to efficiently predict pedestrian crossing intent, and employs a modality-decomposed strategy in which each feature stream is processed independently and integrated via a lightweight meta-classifier.

Chia-Yen Chiang, Yasmin Fathy, G. Slabaugh et al. · Scientific Reports · 0 citations