Paper
22 March 1999 Attentional classification
Ravi Kothari, Thiagarajan Balachander
Author Affiliations +
Abstract
Proposed in this paper is a network which uses basis functions based on products of the input space variables raised to a variable power. These basis functions are introduced in regions of confusion obtained through vector quantization of the input space based on patterns which are erroneously classified by a simple linear classifier. The overall effect is thus of directly generating relevant higher order combinations of the input data in regions of maximum confusion. We present the complete architecture of the network and derive a training algorithm. Results using two synthetic data sets are provided.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ravi Kothari and Thiagarajan Balachander "Attentional classification", Proc. SPIE 3722, Applications and Science of Computational Intelligence II, (22 March 1999); https://doi.org/10.1117/12.342914
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KEYWORDS
Quantization

Neurons

Network architectures

Distortion

Neural networks

Algorithm development

Image classification

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