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Biological computational modellers are becoming increasingly interested in building large, eclectic models, including components on many different computational substrates, both biological and non-biological. At the same time, the rise of the philosophy of embodied modelling is generating a need to deploy biological models as controllers for robots in(More)
Automated personal identification using localized ear images has wide range of civilian and law-enforcement applications. This paper investigates a new approach for more accurate ear recognition and verification problem using the sparse representation of local gray-level orientations. We exploit the computational simplicity of localized Radon transform for(More)
Personal identification from the iris images acquired under less-constrained imaging environment is highly challenging problem but with several important applications in surveillance, image forensics, search for missing children and wandering elderly. In this paper, we develop and formulate a new approach for the iris recognition using hypercomplex(More)
A new algorithm is proposed for robust principal component analysis with predefined sparsity patterns. The algorithm is then applied to separate the singing voice from the instrumental accompaniment using vocal activity information. To evaluate its performance, we construct a new publicly available iKala dataset that features longer durations and higher(More)
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