Abstract
In the paper a method is presented for improving the recognition reliability of backpropagation-type networks, based on the attention shifting technique. The mechanism is turned on in cases when the reliability of the network’s answer is low. The signals reaching the hidden layer are used for selection of image areas which are the most ”doubtful” in the process of recognition by the network. Three methods have been proposed for appending the input vector after shifting the area where the attention is focused. The methods have been tested in the problem of hand-written digits recognition. Noticeable improvement of the recognition reliability has been obtained.
This work has been partially supported by the AGH UST grant No 10.10.120.39.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Itti, L., Koch, C.: Computational Modeling of Visual Attention. Nature Rev. Neuroscience 2, 194–203 (2001)
Graboi, D., Lisman, J.: Recognition by top-down and bottom-up processing in cortex: the control of selective attention. J. Neurophysiol. 90, 798–810 (2003)
Alpaydın, E., Salah, A.A., Akarun, L.: A Selective Attention Based Method for Visual Pattern Recognition with Application to Handwritten Digit Recognition and Face Recognition. IEEE Trans. PAMI 24, 420–425 (2002)
Choi, S., Ban, S., Lee, M.: Biologically Motivated Attention System Using Bottom-up Saliency Map and Top-down Inhibition. Neural Information Processing Letters and Reviews 22 (2004)
Spratling, M.W., Johnson, M.H.: Pre-integration lateral inhibition enhances unsupervised learning. Neural Computation 14, 2157–2179 (2002)
Schwartz, E.L.: Spatial mapping in the primate sensory projection: analytic structure and the relevance to perception. Biological Cybernetics 25, 181–194 (1977)
Weiman, C.F.R.: Tracking Algorithms Using Log-Polar Mapped Image Coordinates. SPIE Intelligent Robots and Computer Vision VIII 1192 (1989)
Sandini, G., Tistarelli, M.: Vision and Space-Variant Sensing. In: Wechsler, H. (ed.) Neural Networks for Perception, Academic Press, San Diego (1992)
Mikrut, Z., Augustyn, G.: Influence of the object representation on the results of character recognition in the car’s license plates. In: Proc. 5th Conf. on Neural Networks and Soft Computing, Zakopane, Poland, pp. 241–246 (2000)
Mikrut, Z.: Recognition of objects normalized in Log-polar space using Kohonen networks. In: Proc. 2nd Int. Symp. on Image and Signal Processing and Analysis, Pula, Croatia, pp. 308–312 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mikrut, Z., Piaskowska, A. (2006). Attention Improves the Recognition Reliability of Backpropagation Network. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science(), vol 4029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11785231_66
Download citation
DOI: https://doi.org/10.1007/11785231_66
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35748-3
Online ISBN: 978-3-540-35750-6
eBook Packages: Computer ScienceComputer Science (R0)