ARTIFICIAL NEURAL NETWORK BASED DISCRIMINATION OF MINELIKE OBJECTS IN INFRARED IMAGES

Por haverem poucos casos tanto em cães como em gatos de classificações histológicas de tecido hematopoiético e linforreticular e de tecido nervoso procedemos à

Results from the clustering procedure based on artificial neural network analysis of 20 sweet corn inbred lines, which evi - denced three genetically differentiated groups.... 89.7%

All artificial neural networks used in this work showed high accuracy to estimate the moisture, however, the neural network based on the basic density and drying days was the

A mulit-layer artificial neural network, with a backpropagation training algorithm and 11 neurons in the input layer, was used.. In this type of network, network inputs are

In this sense, the purpose of this study was to evaluate the feasibility of artificial neural networks as a technique for genetic diversity analysis of Carica papaya L., implementing

Based on the experimental data from the isothermal compressions of 42CrMo high strength steel, an artificial neural network (ANN) was trained with standard back-propagation

In this paper, genetic algorithm based artificial neural network hybrid prediction model is proposed to foretell surface roughness and tool wear.. A multiple

In line with this, artificial neural network technology of backpropagation neural network (BPNN), radial basis function neural network (RBFNN) and generalized regression