Balan, Ajay, N., authorAzimi-Sadjadi, Mahmood R., authorIEEE, publisher2007-01-032007-01-031995Balan, Ajay N. and Mahmood R. Azimi-Sadjadi, Detection and Classification of Buried Dielectric Anomalies by Means of the Bispectrum Method and Neural Networks, IEEE Transactions on Instrumentation and Measurement 44, no. 6 (December 1995): 998-1002.http://hdl.handle.net/10217/859The development of neural network-based system for detection and classification of buried landmines is the main focus of this paper. Shape-dependent features are extracted by means of the bispectrum method. These features are then applied to the neural network. A multilayer back-propagation-type neural network is trained and tested on the feature sets extracted from equally spaced radial slices of image windows. Simulation results obtained for two types of targets indicated good detection and classification rates.born digitalarticleseng©1995 IEEE.Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.multilayer perceptronsmilitary systemsfeature extractionfeedforward neural netsDetection and classification of buried dielectric anomalies by means of the bispectrum method and neural networksText