Mine detection using scattering parameters and an artificial neural network

IEEE Transactions on Neural Networks

Volumn 8, Issue 6, 1997, Pages 1456-1467

  Plett, Gregory L ^a,b   Doi, Takeshi ^b   Torrieri, Don ^a,c  

^a IEEE   (United States)

^b Stanford University   (United States)

^c U S ARMY RESEARCH LABORATORY   (United States)

Author keywords

Anti personnel land mine detection; Dimensionality reduction; Feature extraction; Microwave sensor; Neural network applications; Pattern classification; Statistical outlier removal

Indexed keywords

DATA ACQUISITION; FEATURE EXTRACTION; LEARNING SYSTEMS; MICROWAVE DEVICES; NEURAL NETWORKS; SENSORS;

ANTIPERSONNEL LAND MINE DETECTION; KARHUNEN-LOEVE TRANSFORM; MICROWAVE SENSOR;

DETECTORS;

EID: 0031270610     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.641468     Document Type: Article

References (19)

1. D. A. Bloom, "Land mines keep wars from ever coming to an end," The Christian Science Monitor, vol. 87, no. 57, p. 19, Feb. 1995.
2. D. Webster, "One leg, one life at a time," The New York Times Magazine, Jan. 23, 1994.
3. M. R. Azimi-Sadjadi, D. E. Poole, S. Sheedvash, K. D. Sherbondy, and S. A. Stricker, "Detection and classification of buried dielectric anomalies using a separated aperture sensor and a neural-network discriminator," IEEE Trans. Instrum. Meas., vol. 41, pp. 137-143, Feb. 1992.
4. M. R. Azimi-Sadjadi and S. A. Stricker, "Detection and classification of buried dielectric anomalies using neural networks - Further results," IEEE Trans. Instrum. Meas., vol. 43, pp. 34-39, Feb. 1994.
5. M. A. Lehr, "Adaptive multisource decision-making: Detecting land mines with neural networks using separated aperture sensor data collected at Fort Belvoir," Stanford Univ., CA, Final Rep., U.S. Army Contract DAAK70-89-K-0001, Apr. 1992.
6. L. S. Riggs and C. A. Amazeen, "Research efforts with the waveguide beyond cutoff or separated aperture dielectric anomaly detection scheme," U.S. Army Ft. Belvoir RD&E Center, Ft. Belvoir, VA, Int. Rep. 2497, 1989.
7. F. R. Clague, "Summary of experiments with the separated aperture technique of dielectric anomaly detection, final report," U.S. Army Ft. Belvoir RD&E Center, Ft. Belvoir, VA, Rep SR-723-29-89, 1989.
8. R. O. Duda and P. E. Hart, Pattern Classification and Scene Analysis. New York: Wiley, 1973.
9. K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed. New York: Academic, 1990.
10. R. Schalkoff, Pattern Recognition: Statistical, Structural, and Neural Approaches. New York: Wiley, 1992.
11. B. Widrow and M. A. Lehr, "30 years of adaptive neural networks: Perceptron, Madaline, and backpropagation," Proc. IEEE, Sept. 1990, vol. 78, no. 9, pp. 1415-1442.
12. T. M. Cover and J. A. Thomas, Elements of Information Theory, Wiley series in telecommunications. New York: Wiley, 1991.
13. R. Anand, K. Mehrotra, C. Mohan, and S. Ranka, "An improved algorithm for neural network classification of imbalanced training sets," IEEE Trans. Neural Networks, vol. 4, pp. 962-969, Nov. 1993.
14. D. Torrieri, "A linear transform that simplifies and improves neural-network classifiers," in Proc. ICNN-IEEE Int. Conf. Neural Networks, Washington, D.C., June 1996, pp. 1738-1743.
15. T. Doi and G. L. Plett, "Adaptive neural networks for mine detection; Scientific and technical report," U.S. Army Contract DAAK70-92-K-0003, Stanford Univ., CA, 1995, Final Rep., Available http://www-isl.stanford.edu/people/glp/mines95.ps
16. A. Gersho and R. Gray, Vector Quantization and Signal Compression. Boston, MA: Kluwer, 1992.
17. T. Kohonen et al., "LVQ_PAK: The learning vector quantization program package v 2.1," Available FTP: cochlea.hut.fi (130.233.168.48), Oct. 9, 1992.
18. S. C. Ahalt, A. K. Knshnamurthy, P. Chen, and D. E. Melton, "Competitive learning algorithms for vector quantization," Neural Networks, vol. 3, pp. 277-290, 1990.
19. N. Ueda and R. Nakano, "A competitive and selective learning method for designing optimal vector quantizers," in Proc. ICNN-IEEE Int. Conf. Neural Networks, Mar. 1993, pp. 1444-1450.