A PMJ-inspired cognitive framework for natural scene categorization in line drawings

This paper investigates the computational model of line drawings and proposes a PMJ-inspired cognitive framework for natural scene categorization in line drawings, and shows that the proposed cognitive framework achieves 48.4% recognition rate in leave-one-out cross-validation, much higher than fMRI-data-driven decoding accuracy in the visual-processing hierarchy.