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Improved neural network modeling of inverse lens distortion

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dc.contributor.author De Villiers, JP
dc.contributor.author Cronje, J
dc.contributor.author Nicolls, FC
dc.date.accessioned 2012-01-16T10:55:47Z
dc.date.available 2012-01-16T10:55:47Z
dc.date.issued 2011-04
dc.identifier.citation De Villiers, JP, Cronje, J and Nicolls, FC. 2011. Improved neural network modeling of inverse lens distortion. Defense, Security, and Sensing (DSS11), Orlando World Center Marriott Resort & Convention Centre, Orlando, Florida, USA, 26-28 April 2011, 9 pp en_US
dc.identifier.uri http://hdl.handle.net/10204/5488
dc.description Defense, Security, and Sensing (DSS11), Orlando World Center Marriott Resort & Convention Centre, Orlando, Florida, USA, 26-28 April 2011 en_US
dc.description.abstract Inverse lens distortion modelling allows one to find the pixel in a distorted image which corresponds to a known point in object space, such as may be produced by a RADAR. This paper extends recent work using neural networks as a compromise between processing complexity, memory usage and accuracy. The already encouraging results are further enhanced by considering different neuron activation functions, architectures, scaling methodologies and training techniques. The errors are given in terms of microns on the detector to facilitate fair comparison between different resolutions and pixel sizes. en_US
dc.language.iso en en_US
dc.relation.ispartofseries Workflow request;7182
dc.subject Neural networks en_US
dc.subject Lens distortion en_US
dc.subject Inverse distortion corrections en_US
dc.subject Radar en_US
dc.title Improved neural network modeling of inverse lens distortion en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation De Villiers, J., Cronje, J., & Nicolls, F. (2011). Improved neural network modeling of inverse lens distortion. http://hdl.handle.net/10204/5488 en_ZA
dc.identifier.chicagocitation De Villiers, JP, J Cronje, and FC Nicolls. "Improved neural network modeling of inverse lens distortion." (2011): http://hdl.handle.net/10204/5488 en_ZA
dc.identifier.vancouvercitation De Villiers J, Cronje J, Nicolls F, Improved neural network modeling of inverse lens distortion; 2011. http://hdl.handle.net/10204/5488 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - De Villiers, JP AU - Cronje, J AU - Nicolls, FC AB - Inverse lens distortion modelling allows one to find the pixel in a distorted image which corresponds to a known point in object space, such as may be produced by a RADAR. This paper extends recent work using neural networks as a compromise between processing complexity, memory usage and accuracy. The already encouraging results are further enhanced by considering different neuron activation functions, architectures, scaling methodologies and training techniques. The errors are given in terms of microns on the detector to facilitate fair comparison between different resolutions and pixel sizes. DA - 2011-04 DB - ResearchSpace DP - CSIR KW - Neural networks KW - Lens distortion KW - Inverse distortion corrections KW - Radar LK - https://researchspace.csir.co.za PY - 2011 T1 - Improved neural network modeling of inverse lens distortion TI - Improved neural network modeling of inverse lens distortion UR - http://hdl.handle.net/10204/5488 ER - en_ZA


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