By A. Schuster, J. Nicholson

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However, the FPF has the ability to increase the discrimination and thus the correlation signal of the trees is not as sharp as that of the boy. The remainder of the process merely finds large, sharp peaks to indicate the presence of a target. The peak belonging to the boy in this case is definitely the sharpest peak and now a decision is possible. 50 3 Automated Image Object Recognition Fig. 19. An original image and some of the pulse images. In one of the pulse images the target is the bright object and in another the outline of the target is the bright object Fig.

22 2 Theory of Digital Simulation Fig. 11. 11 displays the results of a PCNN with random initial threshold values. As can be seen, the fast linking method is a tremendously powerful method of reducing noise. It also prevents the network from experiencing segmentation decay. This latter effect may be desired if only segmentation was needed from the PCNN outputs and detrimental if the texture segmentation was desired. 5 Fast Smoothing Perhaps the fastest way to compute the PCNN iterations is to replace both M and W with a smoothing operation.

The input data used for training the networks was obtained from simulated movesequences of each aeroplane. The movie includes large variations in scale and 3D orientation of the aeroplanes. However, not all angles (and scale sizes) were included in the training data. This was done particularly in order to evaluate the generalisation capability of the system. Only the non-zero components of the first period of the PCNN 1D time series were used as input to the subsequent neural networks. 1. The number of inputs was in all cases 43.

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An Introduction to the Theory of Optics by A. Schuster, J. Nicholson

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