1. Automatic Screening of Sonar Imagery Using Artificial Intelligence Techniques John Tran

2. Contents Introduction and Background Development Results and Conclusions

3. Introduction and Background

4. Functionality Analyze sonar images and produce signals of interest Use processed image data instead of raw image Revolves around the application of neural networks with various modifications

5. Background Neural Network –Takes in a number of inputs –Calculates the net internal activity at each node –Apply activation functions to these values –Continue to do this until the end of the network Multilayer Perceptron –Involves multiple layers and possible hidden nodes

6. Related Projects The Truck Backer-Upper (Nguyen and Widrow) –Used a multilayer perceptron network to simulate a trailer truck backing into a loading dock

7. Expected Results Training error over time < 1 Consistent detection spaces Good adaptability of the neural network

8. Related Research The research project being done here was built off of my mentor’s original research on the subject.

9. Development

10. Procedures/Methods Initialization Repeated Review Update

11. Programming Language MATLab –Handles manipulation of matrices quickly and efficiently

12. Algorithms Back Propagation Sigmoidal Nonlinerality Delta-Delta Learning Rule Nguyen-Widrow Initialization

13. Encountered Problems Incorrect image statistics –Statistics did not represent the original sonar image accurately Inconsistent training results –Detection space would fluctuate with each training

14. Results and Conclusions

15. Figures Original Sonar Image Detection Space Output Coordinate Tracker

16. Figures Good CaseAverage CaseBad Case Results

17. Thank you for listening.

18. Works Cited The formatting will be edited later. Simon Haykin - Neural Networks: A Comprehensive Foundation (2nd Edition). Clifford Lau - Neural Networks: Theoretical Foundations and Analysis Yu Hen Hu, Jenq-Neng Hwang - Introduction to Neural Networks for Signal Processing Cohen and Bray, 2007 - Gram Analysis Research Derrick Nguyen and Prof. Bernard Widrow - The Truck Backer-Upper: An Example of Self- Learning in Neural Networks. Derrick Nguyen and Prof. Bernard Widrow - Improving the Learning Speed of 2-Layer Neural Networks by Choosing Initial Values of the Adaptive Weights.