Sequential Simulated Annealing System for Pattern Detection
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Simulated annealing for pattern detection and seismic analysis
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Hough transform neural network for seismic pattern detection
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
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A two-layer neural-network model is designed which accepts image coordinates as the input and learns the parametric form of conoidal shapes (lines/circles/ellipses) adaptively. It provides an efficient representation of visual information embedded in the connection weights and the parameters of the processing elements. It not only reduces the large space requirements of the classical Hough transform (HT), but also represents parameters with a higher precision. The performance of the methodology is compared with other existing algorithms and has been found to excel over those algorithms in many cases