Matches in SemOpenAlex for { <https://semopenalex.org/work/W2897345725> ?p ?o ?g. }
Showing items 1 to 96 of
96
with 100 items per page.
- W2897345725 abstract "Automatic plant species identification is a difficulty challenge and an interesting area of research for both botanical taxonomy and computer science. From the past few years, some attempts towards the development of automatic plant recognition systems have been proposed, but the performance of such systems is not satisfactory in terms of accuracy, and these systems are also task dependent, since they are strongly influenced by the set of characteristics extracted from plant samples, leading to the problem known as data set bias. In this work, we use a Multi-Layer Perceptron (MLP) artificial neural network trained with Backpropagation algorithm to perform automatic plant classification. To avoid data set bias problem, some plant data sets which use different plant features obtained by different feature extraction processes are employed. We compare MLP algorithm with several supervised learning methods from plant recognition literature using a statistical hypothesis test of type Friedman/Nemenyi test. The obtained results show the potential of MLP algorithm to deal with plant classification in a unbiased fashion." @default.
- W2897345725 created "2018-10-26" @default.
- W2897345725 creator A5029164446 @default.
- W2897345725 creator A5037129186 @default.
- W2897345725 creator A5044613127 @default.
- W2897345725 date "2018-07-01" @default.
- W2897345725 modified "2023-10-04" @default.
- W2897345725 title "Plant Classification Using Artificial Neural Networks" @default.
- W2897345725 cites W1971057867 @default.
- W2897345725 cites W1974758710 @default.
- W2897345725 cites W1991286329 @default.
- W2897345725 cites W2016944307 @default.
- W2897345725 cites W2030432742 @default.
- W2897345725 cites W2031342017 @default.
- W2897345725 cites W2077991880 @default.
- W2897345725 cites W2121305270 @default.
- W2897345725 cites W2162506329 @default.
- W2897345725 cites W2176949197 @default.
- W2897345725 cites W2213241010 @default.
- W2897345725 cites W2329838488 @default.
- W2897345725 cites W2564711569 @default.
- W2897345725 cites W2598459425 @default.
- W2897345725 cites W2735277995 @default.
- W2897345725 cites W2766736793 @default.
- W2897345725 cites W93718877 @default.
- W2897345725 doi "https://doi.org/10.1109/ijcnn.2018.8489701" @default.
- W2897345725 hasPublicationYear "2018" @default.
- W2897345725 type Work @default.
- W2897345725 sameAs 2897345725 @default.
- W2897345725 citedByCount "12" @default.
- W2897345725 countsByYear W28973457252019 @default.
- W2897345725 countsByYear W28973457252020 @default.
- W2897345725 countsByYear W28973457252021 @default.
- W2897345725 countsByYear W28973457252022 @default.
- W2897345725 countsByYear W28973457252023 @default.
- W2897345725 crossrefType "proceedings-article" @default.
- W2897345725 hasAuthorship W2897345725A5029164446 @default.
- W2897345725 hasAuthorship W2897345725A5037129186 @default.
- W2897345725 hasAuthorship W2897345725A5044613127 @default.
- W2897345725 hasConcept C116834253 @default.
- W2897345725 hasConcept C119857082 @default.
- W2897345725 hasConcept C136389625 @default.
- W2897345725 hasConcept C153180895 @default.
- W2897345725 hasConcept C154945302 @default.
- W2897345725 hasConcept C155032097 @default.
- W2897345725 hasConcept C169903167 @default.
- W2897345725 hasConcept C177264268 @default.
- W2897345725 hasConcept C179717631 @default.
- W2897345725 hasConcept C199360897 @default.
- W2897345725 hasConcept C24412817 @default.
- W2897345725 hasConcept C2776091240 @default.
- W2897345725 hasConcept C41008148 @default.
- W2897345725 hasConcept C41806617 @default.
- W2897345725 hasConcept C50644808 @default.
- W2897345725 hasConcept C52622490 @default.
- W2897345725 hasConcept C58642233 @default.
- W2897345725 hasConcept C59822182 @default.
- W2897345725 hasConcept C60908668 @default.
- W2897345725 hasConcept C86803240 @default.
- W2897345725 hasConceptScore W2897345725C116834253 @default.
- W2897345725 hasConceptScore W2897345725C119857082 @default.
- W2897345725 hasConceptScore W2897345725C136389625 @default.
- W2897345725 hasConceptScore W2897345725C153180895 @default.
- W2897345725 hasConceptScore W2897345725C154945302 @default.
- W2897345725 hasConceptScore W2897345725C155032097 @default.
- W2897345725 hasConceptScore W2897345725C169903167 @default.
- W2897345725 hasConceptScore W2897345725C177264268 @default.
- W2897345725 hasConceptScore W2897345725C179717631 @default.
- W2897345725 hasConceptScore W2897345725C199360897 @default.
- W2897345725 hasConceptScore W2897345725C24412817 @default.
- W2897345725 hasConceptScore W2897345725C2776091240 @default.
- W2897345725 hasConceptScore W2897345725C41008148 @default.
- W2897345725 hasConceptScore W2897345725C41806617 @default.
- W2897345725 hasConceptScore W2897345725C50644808 @default.
- W2897345725 hasConceptScore W2897345725C52622490 @default.
- W2897345725 hasConceptScore W2897345725C58642233 @default.
- W2897345725 hasConceptScore W2897345725C59822182 @default.
- W2897345725 hasConceptScore W2897345725C60908668 @default.
- W2897345725 hasConceptScore W2897345725C86803240 @default.
- W2897345725 hasLocation W28973457251 @default.
- W2897345725 hasOpenAccess W2897345725 @default.
- W2897345725 hasPrimaryLocation W28973457251 @default.
- W2897345725 hasRelatedWork W2013585556 @default.
- W2897345725 hasRelatedWork W2054058245 @default.
- W2897345725 hasRelatedWork W2150138875 @default.
- W2897345725 hasRelatedWork W2600618515 @default.
- W2897345725 hasRelatedWork W2897345725 @default.
- W2897345725 hasRelatedWork W3010425320 @default.
- W2897345725 hasRelatedWork W3201511606 @default.
- W2897345725 hasRelatedWork W4231994957 @default.
- W2897345725 hasRelatedWork W749491080 @default.
- W2897345725 hasRelatedWork W2284565437 @default.
- W2897345725 isParatext "false" @default.
- W2897345725 isRetracted "false" @default.
- W2897345725 magId "2897345725" @default.
- W2897345725 workType "article" @default.