Abstract
We introduce new methods for creation of a dictionary of features for a biologically inspired model of visual object classification that is shown to handle the recognition of several object categories. We provide a new method for creation of this features dictionary using non-supervised cortex like methods. Different clustering approaches were experimented and improved performance is achieved on image centers which results in real time classification of images by HMAX model.
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Jalali, S., Lim, J.H., Ong, S.H., Tham, J.Y. (2010). Dictionary of Features in a Biologically Inspired Approach to Image Classification. In: Wong, K.W., Mendis, B.S.U., Bouzerdoum, A. (eds) Neural Information Processing. Models and Applications. ICONIP 2010. Lecture Notes in Computer Science, vol 6444. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17534-3_67
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DOI: https://doi.org/10.1007/978-3-642-17534-3_67
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17533-6
Online ISBN: 978-3-642-17534-3
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