%0 Computer Program %A Alameer, Ali %A Degenaar, Patrick %A Nazarpour, Kianoush %D 2019 %T A Matlab code that runs a proposed biologically-inspired hierarchical architecture for object and scene recognition %U https://data.ncl.ac.uk/articles/software/Code_zip/11336990 %R 10.25405/data.ncl.11336990.v2 %2 https://data.ncl.ac.uk/ndownloader/files/20099501 %K En-HMAX %K Machine vision %K Deep learning neural network %K Electrical and Electronic Engineering not elsewhere classified %X This Matlab code runs our recently-developed model, that is, the elastic net-regularized hierarchical MAX (En-HMAX). With this model, classification accuracies of up to 90% for objects and scenes image datasets were possible. Modelling human experiments, window and scotoma analysis with the En-HMAX model revealed that object and scene recognition are sensitive to the availability of data in the centre and the periphery of the images, respectively. The En-HMAX model adopts a relative order of importance, similar to the human visual system, depending on the image category. %I Newcastle University