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Infra-red Face Recognition Using Ensemble Back-propagation Neural Networks

Benyamin Kusumoputro, Lina Lina


Various kinds of Unmanned Aerial Vehicles (UAV) are developed for many purposes, and numerous studies concerning with the development of components and its applications arises considerably. The present paper addresses the development of a face recognition system and its incorporating into a UAV system for security application. We present an approach by using the ensemble neural networks with negative correlation learning based on quadratic error function for recognizing an unlearned face images. An infra-red camera system is utilized, and various experimental set-ups are conducted for studying the performance of the developed algorithms. Karhunen-Loeve method is firstly applied to transform the problem space from its original image space into eigenspace using principal component analysis method. An ensemble neural networks is then applied and analyzed the system’s performance through the Non-optimized and Optimized configuration scenarios. Experiment results show that the recognition rate of the developed system could reach as high as 99.9% when using a database consists of 10 Indonesian persons.

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