Lineaments recognition for potential fields images using a learning algorithm for Boltzmann machines
G. Cartabia, Andrea Zerilli, Bruno Apolloni · 1994
PreviousNext No AccessSEG Technical Program Expanded Abstracts 1994Lineaments recognition for potential fields images using a learning algorithm for Boltzmann machinesAuthors: G. CartabiaA. ZerilliB. ApolloniG. CartabiaUniversity of Milan, A. ZerilliAgip Milan, and B. ApolloniUniversity of Milanhttps://doi.org/10.1190/1.1932118 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Permalink: https://doi.org/10.1190/1.1932118FiguresReferencesRelatedDetailsCited ByInverse Theory, Artificial Neural Networks27 May 2021Inverse Theory: Artificial Neural Networks25 August 2020Neural networks as an intelligence amplification tool: A review of applicationsMary M. Poulton24 May 2002 | GEOPHYSICS, Vol. 67, No. 3Estimating one-dimensional models from frequency-domain electromagnetic data using modular neural networksIEEE Transactions on Geoscience and Remote Sensing, Vol. 36, No. 2 SEG Technical Program Expanded Abstracts 1994ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 1994 Pages: 1679 publication data© 1994 Copyright © 1994 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished: 10 Feb 2005 CITATION INFORMATION G. Cartabia, A. Zerilli, and B. Apolloni, (1994), "Lineaments recognition for potential fields images using a learning algorithm for Boltzmann machines," SEG Technical Program Expanded Abstracts : 432-435. https://doi.org/10.1190/1.1932118 Plain-Language Summary PDF DownloadLoading ...