Processing occlusions using elastic-net hierarchical MAX model of the visual cortex

Abstract

Humans can recognise objects under partial occlusion. Machine-based approaches cannot reliably recognise objects and scenes in the presence of occlusion. This paper investigates the use of the elastic net hierarchical MAX (En-HMAX) model to handle occlusions. Our experiments show that the En-HMAX model achieves an accuracy of ∼70%, when ∼50% artificial… (More)
DOI: 10.1109/INISTA.2017.8001150

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