Abstract Neural networks, simply stated, are machines that learn. A neural network consisting of several neurons, which are modeled after the human brain, uses synaptic weights, or interneuron connection strengths, to store acquired knowledge, which can be used in the future. One form of neural networks, feedforward networks, uses multilayer perceptrons, which are layered sets of neurons. This type of network contains an input layer, one or more hidden layers, and an output layer. Further, these...

Abstract The enclosed project contains the results of the research, analysis and testing of a Modified Boosting Algorithm to be used by a configuration of learning machines in order to perform regression. The algorithm is used to construct a set of "weak learners", whose individual performance is only slightly better than 50%, but whose ensemble performance is better than any one regression machine. The intent is to develop the algorithm and to demonstrate that it performs as well, if...

Abstract

This thesis addresses the issue of recognizing the hand signs of American Sign Language utilizing deep learning artificial intelligence techniques. The recognition rates of sample data was measured after sample data was prepared in one of three ways: normalizing the image, coverting to binary black and white, and color with background removed. Of the three, this thesis showed that recognition is best with color and background removed.