Matches in SemOpenAlex for { <https://semopenalex.org/work/W2892829030> ?p ?o ?g. }
Showing items 1 to 95 of
95
with 100 items per page.
- W2892829030 abstract "Hyperspectral images are data cubes that offer very rich spectral and spatial resolutions. These images are so highly dimensioned that we generally reduce them in a pre-processing step in order to process them efficiently. In this context, Local Fisher Discriminant Analysis (LFDA) is a feature extraction technique that proved better than several commonly used dimensionality reduction techniques. However, this method suffers from memory problems and long execution times on commodity hardware. In this paper, to solve these problems, we first added an optimization step to LFDA to make it executable on commodity hardware and to make it suitable for parallel and distributed computing, then, we implemented it in a parallel and distributed way using Apache Spark. We tested our implementation on Amazon Web Services (AWS)’s Elastic MapReduce (EMR) clusters, using different hyperspectral images with different sizes. This proved higher performances with a speedup of up to 70x." @default.
- W2892829030 created "2018-10-05" @default.
- W2892829030 creator A5056830039 @default.
- W2892829030 creator A5063197263 @default.
- W2892829030 creator A5074532435 @default.
- W2892829030 date "2018-01-01" @default.
- W2892829030 modified "2023-09-26" @default.
- W2892829030 title "Parallel and Distributed Local Fisher Discriminant Analysis to Reduce Hyperspectral Images on Cloud Computing Architectures" @default.
- W2892829030 cites W2001619934 @default.
- W2892829030 cites W2030912027 @default.
- W2892829030 cites W2053437444 @default.
- W2892829030 cites W2094412456 @default.
- W2892829030 cites W2110114082 @default.
- W2892829030 cites W2115669554 @default.
- W2892829030 cites W2119897980 @default.
- W2892829030 cites W2151599207 @default.
- W2892829030 cites W2338459354 @default.
- W2892829030 cites W2406982333 @default.
- W2892829030 cites W2521008014 @default.
- W2892829030 cites W2532852010 @default.
- W2892829030 cites W2594469973 @default.
- W2892829030 cites W2772822977 @default.
- W2892829030 doi "https://doi.org/10.1007/978-3-030-01449-0_21" @default.
- W2892829030 hasPublicationYear "2018" @default.
- W2892829030 type Work @default.
- W2892829030 sameAs 2892829030 @default.
- W2892829030 citedByCount "3" @default.
- W2892829030 countsByYear W28928290302019 @default.
- W2892829030 countsByYear W28928290302020 @default.
- W2892829030 countsByYear W28928290302021 @default.
- W2892829030 crossrefType "book-chapter" @default.
- W2892829030 hasAuthorship W2892829030A5056830039 @default.
- W2892829030 hasAuthorship W2892829030A5063197263 @default.
- W2892829030 hasAuthorship W2892829030A5074532435 @default.
- W2892829030 hasConcept C111919701 @default.
- W2892829030 hasConcept C124101348 @default.
- W2892829030 hasConcept C151730666 @default.
- W2892829030 hasConcept C153180895 @default.
- W2892829030 hasConcept C154945302 @default.
- W2892829030 hasConcept C159078339 @default.
- W2892829030 hasConcept C160145156 @default.
- W2892829030 hasConcept C173608175 @default.
- W2892829030 hasConcept C199360897 @default.
- W2892829030 hasConcept C2779343474 @default.
- W2892829030 hasConcept C2781215313 @default.
- W2892829030 hasConcept C41008148 @default.
- W2892829030 hasConcept C52622490 @default.
- W2892829030 hasConcept C68339613 @default.
- W2892829030 hasConcept C70518039 @default.
- W2892829030 hasConcept C79974875 @default.
- W2892829030 hasConcept C86803240 @default.
- W2892829030 hasConceptScore W2892829030C111919701 @default.
- W2892829030 hasConceptScore W2892829030C124101348 @default.
- W2892829030 hasConceptScore W2892829030C151730666 @default.
- W2892829030 hasConceptScore W2892829030C153180895 @default.
- W2892829030 hasConceptScore W2892829030C154945302 @default.
- W2892829030 hasConceptScore W2892829030C159078339 @default.
- W2892829030 hasConceptScore W2892829030C160145156 @default.
- W2892829030 hasConceptScore W2892829030C173608175 @default.
- W2892829030 hasConceptScore W2892829030C199360897 @default.
- W2892829030 hasConceptScore W2892829030C2779343474 @default.
- W2892829030 hasConceptScore W2892829030C2781215313 @default.
- W2892829030 hasConceptScore W2892829030C41008148 @default.
- W2892829030 hasConceptScore W2892829030C52622490 @default.
- W2892829030 hasConceptScore W2892829030C68339613 @default.
- W2892829030 hasConceptScore W2892829030C70518039 @default.
- W2892829030 hasConceptScore W2892829030C79974875 @default.
- W2892829030 hasConceptScore W2892829030C86803240 @default.
- W2892829030 hasLocation W28928290301 @default.
- W2892829030 hasOpenAccess W2892829030 @default.
- W2892829030 hasPrimaryLocation W28928290301 @default.
- W2892829030 hasRelatedWork W126394981 @default.
- W2892829030 hasRelatedWork W1483680804 @default.
- W2892829030 hasRelatedWork W1677208095 @default.
- W2892829030 hasRelatedWork W1865067283 @default.
- W2892829030 hasRelatedWork W1974165158 @default.
- W2892829030 hasRelatedWork W1991937878 @default.
- W2892829030 hasRelatedWork W2013384463 @default.
- W2892829030 hasRelatedWork W2046489888 @default.
- W2892829030 hasRelatedWork W2063512404 @default.
- W2892829030 hasRelatedWork W2063922845 @default.
- W2892829030 hasRelatedWork W2066279123 @default.
- W2892829030 hasRelatedWork W2078410682 @default.
- W2892829030 hasRelatedWork W2097568515 @default.
- W2892829030 hasRelatedWork W2188513145 @default.
- W2892829030 hasRelatedWork W2338459354 @default.
- W2892829030 hasRelatedWork W2488461070 @default.
- W2892829030 hasRelatedWork W2510026128 @default.
- W2892829030 hasRelatedWork W2607376878 @default.
- W2892829030 hasRelatedWork W2952069359 @default.
- W2892829030 hasRelatedWork W2963220077 @default.
- W2892829030 isParatext "false" @default.
- W2892829030 isRetracted "false" @default.
- W2892829030 magId "2892829030" @default.
- W2892829030 workType "book-chapter" @default.