Title:
A Multi-Stage Neural Network for Automatic Target Detection

dc.contributor.author Howard, Ayanna M. en_US
dc.contributor.author Padgett, Curtis en_US
dc.contributor.author Liebe, Carl Christian en_US
dc.contributor.corporatename Jet Propulsion Laboratory (U.S.) en_US
dc.contributor.corporatename Georgia Institute of Technology. Center for Robotics and Intelligent Machines en_US
dc.date.accessioned 2011-04-05T18:06:15Z
dc.date.available 2011-04-05T18:06:15Z
dc.date.issued 1998-05
dc.description ©1998 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. en_US
dc.description Presented at the 1998 International Joint Conference on Neural Networks (IJCNN) Anchorage, Alaska, May 1998. en_US
dc.description DOI: 10.1109/IJCNN.1998.682268 en_US
dc.description.abstract Automatic Target Recognition (ATR) involves processing two-dimensional images for detecting, classifying, and tracking targets. The first stage in ATR is the detection process. This involves discrimination between target and non-target objects in a scene. In this paper, we shall discuss a novel approach which addresses the target detection process. This method extracts relevant object features utilizing principal component analysis. These extracted features are then presented to a multi-stage neural network which allows an overall increase in detection rate, while decreasing the false positive alarm rate. We shall discuss the techniques involved and present some detection results that have been implemented on the multi-stage neural network. en_US
dc.identifier.citation A. Howard, C. Padgett, C. Liebe, “A Multi-Stage Neural Network for Automatic Target Detection,” The 1998 IEEE International Joint Conference on Neural Networks (IJCNN) Anchorage, Alaska, May 1998, Vol. 1, 231-236. en_US
dc.identifier.doi 10.1109/IJCNN.1998.682268
dc.identifier.isbn 0-7803-4859-1
dc.identifier.uri http://hdl.handle.net/1853/38381
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.publisher.original Institute of Electrical and Electronics Engineers en_US
dc.subject Target recognition en_US
dc.subject Neural networks en_US
dc.subject Detection en_US
dc.title A Multi-Stage Neural Network for Automatic Target Detection en_US
dc.type Text
dc.type.genre Proceedings
dspace.entity.type Publication
local.contributor.author Howard, Ayanna M.
local.contributor.corporatename School of Civil and Environmental Engineering
local.contributor.corporatename Institute for Robotics and Intelligent Machines (IRIM)
relation.isAuthorOfPublication 6d77e175-105c-4b0b-9548-31f20e60e20a
relation.isOrgUnitOfPublication 88639fad-d3ae-4867-9e7a-7c9e6d2ecc7c
relation.isOrgUnitOfPublication 66259949-abfd-45c2-9dcc-5a6f2c013bcf
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