Selective Attention for Robust Recognition of Noisy and Superimposed Patterns

Based on the “early selection” filter model, a new selective attention algorithm is developed to improve recognition performance for noisy patterns and superimposed patterns. The selective attention algorithm incorporates the error backpropagation rule to adapt the attention filters for a testing input pattern and an attention cue for a specific class. For superimposed test patterns an attention-switching algorithm is also developed to recognize both patterns one by one. The developed algorithms demonstrated much higher recognition rates for corrupted digit recognition tasks.

[1]  N. Cowan.  Evolving conceptions of memory storage, selective attention, and their mutual constraints within the human information-processing system. , 1988, Psychological bulletin.

[2]  D. Broadbent.  Perception and communication , 1958 .

[3]  A. Treisman.  Contextual Cues in Selective Listening , 1960 .

[4]  Donald E. Broadbent,et al.  Decision and stress , 1971 .

[5]  W. Johnston,et al.  Flexibility and capacity demands of attention , 1978 .

[6]  H. Pashler.  The Psychology of Attention , 1997 .

[7]  Soo-Young Lee,et al.  TAG: A Neural Network Model for Large-Scale Optical Implementation , 1991, Neural Computation.

[8]  K. Fukushima.  Neural network model for selective attention in visual pattern recognition and associative recall. , 1987, Applied optics.

[9]  S Y Lee,et al.  Optical implementation of associative memory with controlled bit-significance. , 1988, Applied optics.

[10]  N. Cowan.  Attention and Memory: An Integrated Framework , 1995 .

[11]  K. H. Ahn,et al.  Voice Command II: A DSP Implementation of Robust Speech Recognition in Real-World Noisy Environments , 1997, ICONIP.

[12]  J. Deutsch,et al.  Attention: Some theoretical considerations. , 1963 .

[13]  R. Parasuraman.  The attentive brain in aging and Alzheimer's disease. , 1998 .

[14]  J. Kruschke,et al.  ALCOVE: an exemplar-based connectionist model of category learning. , 1992, Psychological review.

[15]  M. Posner,et al.  Attention and cognitive control. , 1975 .

[16]  Rajesh P. N. Rao.  Correlates of Attention in a Model of Dynamic Visual Recognition , 1997, NIPS.