Yasmin Fathy

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.