Matches in SemOpenAlex for { <https://semopenalex.org/work/W3018582593> ?p ?o ?g. }
Showing items 1 to 100 of
100
with 100 items per page.
- W3018582593 abstract "Abstract Although Convolutional neural networks (CNNs) are widely used for plant disease detection, they require a large number of training samples while dealing with wide variety of heterogeneous background. In this paper, a CNN based dual phase method has been proposed which can work effectively on small rice grain disease dataset with heterogeneity. At the first phase, Faster RCNN method is applied for cropping out the significant portion (rice grain) from an image. This initial phase results in a secondary dataset of rice grains devoid of heterogeneous background. Disease classification is performed on such derived and simplified samples using CNN architecture. Comparison of the dual phase approach with straight forward application of CNN on the small grain dataset shows the effectiveness of the proposed method which provides a 5 fold cross validation accuracy of 88.92%." @default.
- W3018582593 created "2020-05-01" @default.
- W3018582593 creator A5030317765 @default.
- W3018582593 creator A5033438760 @default.
- W3018582593 creator A5041951500 @default.
- W3018582593 date "2021-01-01" @default.
- W3018582593 modified "2023-10-06" @default.
- W3018582593 title "Rice grain disease identification using dual phase convolutional neural network based system aimed at small dataset." @default.
- W3018582593 cites W1686810756 @default.
- W3018582593 cites W1980474730 @default.
- W3018582593 cites W1987161814 @default.
- W3018582593 cites W1992651630 @default.
- W3018582593 cites W2050578633 @default.
- W3018582593 cites W2073600426 @default.
- W3018582593 cites W2078063560 @default.
- W3018582593 cites W2167828202 @default.
- W3018582593 cites W2183341477 @default.
- W3018582593 cites W2191179271 @default.
- W3018582593 cites W2194775991 @default.
- W3018582593 cites W2270641383 @default.
- W3018582593 cites W2414379662 @default.
- W3018582593 cites W2520102481 @default.
- W3018582593 cites W2531409750 @default.
- W3018582593 cites W2577267683 @default.
- W3018582593 cites W2613718673 @default.
- W3018582593 cites W2614850301 @default.
- W3018582593 cites W2731165298 @default.
- W3018582593 cites W2786512734 @default.
- W3018582593 cites W2789255992 @default.
- W3018582593 cites W2887902433 @default.
- W3018582593 cites W2892846124 @default.
- W3018582593 cites W2902625477 @default.
- W3018582593 cites W2954996726 @default.
- W3018582593 cites W2962684187 @default.
- W3018582593 cites W2974299755 @default.
- W3018582593 cites W3130162935 @default.
- W3018582593 doi "https://doi.org/10.31220/agrirxiv.2021.00062" @default.
- W3018582593 hasPublicationYear "2021" @default.
- W3018582593 type Work @default.
- W3018582593 sameAs 3018582593 @default.
- W3018582593 citedByCount "8" @default.
- W3018582593 countsByYear W30185825932020 @default.
- W3018582593 countsByYear W30185825932021 @default.
- W3018582593 countsByYear W30185825932022 @default.
- W3018582593 crossrefType "journal-article" @default.
- W3018582593 hasAuthorship W3018582593A5030317765 @default.
- W3018582593 hasAuthorship W3018582593A5033438760 @default.
- W3018582593 hasAuthorship W3018582593A5041951500 @default.
- W3018582593 hasBestOaLocation W30185825931 @default.
- W3018582593 hasConcept C116834253 @default.
- W3018582593 hasConcept C119857082 @default.
- W3018582593 hasConcept C124952713 @default.
- W3018582593 hasConcept C142362112 @default.
- W3018582593 hasConcept C153180895 @default.
- W3018582593 hasConcept C154945302 @default.
- W3018582593 hasConcept C178790620 @default.
- W3018582593 hasConcept C185592680 @default.
- W3018582593 hasConcept C2780980858 @default.
- W3018582593 hasConcept C2992726227 @default.
- W3018582593 hasConcept C41008148 @default.
- W3018582593 hasConcept C44280652 @default.
- W3018582593 hasConcept C59822182 @default.
- W3018582593 hasConcept C6557445 @default.
- W3018582593 hasConcept C81363708 @default.
- W3018582593 hasConcept C86803240 @default.
- W3018582593 hasConceptScore W3018582593C116834253 @default.
- W3018582593 hasConceptScore W3018582593C119857082 @default.
- W3018582593 hasConceptScore W3018582593C124952713 @default.
- W3018582593 hasConceptScore W3018582593C142362112 @default.
- W3018582593 hasConceptScore W3018582593C153180895 @default.
- W3018582593 hasConceptScore W3018582593C154945302 @default.
- W3018582593 hasConceptScore W3018582593C178790620 @default.
- W3018582593 hasConceptScore W3018582593C185592680 @default.
- W3018582593 hasConceptScore W3018582593C2780980858 @default.
- W3018582593 hasConceptScore W3018582593C2992726227 @default.
- W3018582593 hasConceptScore W3018582593C41008148 @default.
- W3018582593 hasConceptScore W3018582593C44280652 @default.
- W3018582593 hasConceptScore W3018582593C59822182 @default.
- W3018582593 hasConceptScore W3018582593C6557445 @default.
- W3018582593 hasConceptScore W3018582593C81363708 @default.
- W3018582593 hasConceptScore W3018582593C86803240 @default.
- W3018582593 hasLocation W30185825931 @default.
- W3018582593 hasLocation W30185825932 @default.
- W3018582593 hasOpenAccess W3018582593 @default.
- W3018582593 hasPrimaryLocation W30185825931 @default.
- W3018582593 hasRelatedWork W2175746458 @default.
- W3018582593 hasRelatedWork W2613736958 @default.
- W3018582593 hasRelatedWork W2732542196 @default.
- W3018582593 hasRelatedWork W2738221750 @default.
- W3018582593 hasRelatedWork W2760085659 @default.
- W3018582593 hasRelatedWork W2883200793 @default.
- W3018582593 hasRelatedWork W3012978760 @default.
- W3018582593 hasRelatedWork W3027997911 @default.
- W3018582593 hasRelatedWork W3093612317 @default.
- W3018582593 hasRelatedWork W4287776258 @default.
- W3018582593 hasVolume "2021" @default.
- W3018582593 isParatext "false" @default.
- W3018582593 isRetracted "false" @default.
- W3018582593 magId "3018582593" @default.
- W3018582593 workType "article" @default.