Abstract
The concept of selective attention as a useful mechanism in Artificial Neural Network models of visual pattern recognition has received a lot of attention recently, particularly since it was found that such a mechanism influences the receptive field profiles of cells in the primate visual pathway by filtering out non-relevant stimuli [28, 29]. It is believed that the massive feedback pathways in the brain play a role in attentional mechanisms by biasing the competition amongst the neural populations that are activated by different parts of a scene [8, 14, 15].
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Lozo, P., Westmacott, J., Do, Q.V., Jain, L.C., Wu, L. (2004). Selective Attention Adaptive Resonance Theory and Object Recognition. In: Fulcher, J., Jain, L.C. (eds) Applied Intelligent Systems. Studies in Fuzziness and Soft Computing, vol 153. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39972-8_10
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DOI: https://doi.org/10.1007/978-3-540-39972-8_10
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