This research study proposes a novel method of inter-related problems in face recognition using the NeuCube neuromorphic computational platform. We investigated age classification and gender recognition. The well-known FG-NET and MORPH Album 2 image gallery were used and anthropometric features were extracted from landmark points on the face. The landmarks were pre-processed with the procrustes algorithm before feature extraction was performed. The Weka machine learning workbench was used to compare the performance of traditional techniques such as the K nearest neighbor (Knn) and Multi-LayerPerceptron (MLP) with NeuCube. Our empirical results show that NeuCube performed consistently better across both problem types that we investigated.
Evolving Systems – Springer Journals
Published: Feb 17, 2017
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