Applications of Artificial Neural Networks III: 21-24 April 1992, Orlando, Florida, Part 1Steven K. Rogers |
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Contents
Largecapacity neural nets for scene analysis Plenary Paper 170903 | 3 |
Authenticity detection in image classification Poster Paper 170929 | 29 |
LowLevel Vision Applications | 33 |
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analysis applications approach architecture artificial neural network artificial neuron backpropagation backpropagation neural network binary blur Boltzmann machine boundary BPNN cell character recognition classes CMAC codebook coding complex compression Computer constraints convergence data association dendritic digits discrimination distortion distortion measure dynamic edge contour edge detection encoding equation error feature extraction filter functional-link gradient hidden layer hidden nodes IEEE Trans image processing implementation initial input layer input pattern input vector invariant iteration learning algorithm linear matching matrix method multilayer perceptron Neocognitron neural net neuron noise nonlinear object obtained optimal orientation output layer output nodes parameters pattern recognition Perceptron performance pixels plane problem receptive field representation represents rotation scale segmentation selected shown in Figure signal simulation spatial structure Subnet supervised learning synapses target techniques texture threshold training patterns training samples training set transform values vector quantizer weights