Roxanne Mirabal-Beltran, Kelsey Rondini, Laura Linnan
Laundromats: Community-Based Partnerships to Increase Reproductive Health Literacy Outreach
Health promotion practice
texture similarity plays important roles texture analysis material recognition however perceptuallyconsistent finegrained texture similarity prediction still challenging discrepancy texture similarity data obtained using algorithms human visual perception demonstrated dilemma normally attributed texture representation similarity metric utilised algorithms inconsistent human perception address challenge introduce perceptionaware texture similarity prediction network patspnet network comprises bilinear lateral attention transformer network bilavit novel loss function namely rsloss bilavit contains siamese feature extraction subnetwork sfen metric learning subnetwork mln designed top mechanisms human perception hand rsloss measures ranking scaling differences knowledge either bilavit rsloss explored texture similarity tasks patspnet performs better least comparably counterparts three data sets different finegrained texture similarity prediction tasks believe promising result due joint utilization bilavit rsloss able learn perceptionaware texture representation similarity metric