Matches in SemOpenAlex for { <https://semopenalex.org/work/W4310792301> ?p ?o ?g. }
Showing items 1 to 74 of
74
with 100 items per page.
- W4310792301 endingPage "108492" @default.
- W4310792301 startingPage "108492" @default.
- W4310792301 abstract "The manual inspections of plant diseases resulted in low accuracy with high time consumption and unable to predict the multiple diseases of plants. To address these difficulties, it is necessary to develop automated systems that are capable of effectively classifying. Therefore, this article presents a customized PDICNet model for plant leaf disease identification and classification. Initially, ResNet-50 is used to extract multiple features from plant leaf images with colour and texture properties. In addition, the modified Red Deer optimization algorithm (MRDOA) is implemented as an optimal feature selection algorithm to obtain optimized and salient features with a reduced size of the MRDOA. Further, a deep learning convolutional neural network (DLCNN) classifier model is utilized to achieve enhanced classification performance. Obtained simulation outcome discloses the superiority of proposed PDICNet model with an accuracy and F1-score of 99.73%, and 99.78%, respectively for PlantVillage dataset and 99.68%, and 99.71% for Rice Plant dataset." @default.
- W4310792301 created "2022-12-17" @default.
- W4310792301 creator A5014600568 @default.
- W4310792301 creator A5023295537 @default.
- W4310792301 creator A5079340619 @default.
- W4310792301 date "2023-01-01" @default.
- W4310792301 modified "2023-10-17" @default.
- W4310792301 title "Resnet-based modified red deer optimization with DLCNN classifier for plant disease identification and classification" @default.
- W4310792301 cites W2162772680 @default.
- W4310792301 cites W2598645336 @default.
- W4310792301 cites W2789255992 @default.
- W4310792301 cites W2795016359 @default.
- W4310792301 cites W2884416373 @default.
- W4310792301 cites W2899663673 @default.
- W4310792301 cites W2901380936 @default.
- W4310792301 cites W2902625477 @default.
- W4310792301 cites W2907625092 @default.
- W4310792301 cites W2927613875 @default.
- W4310792301 cites W2982381523 @default.
- W4310792301 cites W3010225408 @default.
- W4310792301 cites W3010358965 @default.
- W4310792301 cites W3015562698 @default.
- W4310792301 cites W3048692250 @default.
- W4310792301 cites W3095523211 @default.
- W4310792301 cites W3136563782 @default.
- W4310792301 cites W3181256602 @default.
- W4310792301 doi "https://doi.org/10.1016/j.compeleceng.2022.108492" @default.
- W4310792301 hasPublicationYear "2023" @default.
- W4310792301 type Work @default.
- W4310792301 citedByCount "11" @default.
- W4310792301 countsByYear W43107923012023 @default.
- W4310792301 crossrefType "journal-article" @default.
- W4310792301 hasAuthorship W4310792301A5014600568 @default.
- W4310792301 hasAuthorship W4310792301A5023295537 @default.
- W4310792301 hasAuthorship W4310792301A5079340619 @default.
- W4310792301 hasConcept C108583219 @default.
- W4310792301 hasConcept C119857082 @default.
- W4310792301 hasConcept C148483581 @default.
- W4310792301 hasConcept C153180895 @default.
- W4310792301 hasConcept C154945302 @default.
- W4310792301 hasConcept C2780719617 @default.
- W4310792301 hasConcept C2944601119 @default.
- W4310792301 hasConcept C41008148 @default.
- W4310792301 hasConcept C81363708 @default.
- W4310792301 hasConcept C95623464 @default.
- W4310792301 hasConceptScore W4310792301C108583219 @default.
- W4310792301 hasConceptScore W4310792301C119857082 @default.
- W4310792301 hasConceptScore W4310792301C148483581 @default.
- W4310792301 hasConceptScore W4310792301C153180895 @default.
- W4310792301 hasConceptScore W4310792301C154945302 @default.
- W4310792301 hasConceptScore W4310792301C2780719617 @default.
- W4310792301 hasConceptScore W4310792301C2944601119 @default.
- W4310792301 hasConceptScore W4310792301C41008148 @default.
- W4310792301 hasConceptScore W4310792301C81363708 @default.
- W4310792301 hasConceptScore W4310792301C95623464 @default.
- W4310792301 hasLocation W43107923011 @default.
- W4310792301 hasOpenAccess W4310792301 @default.
- W4310792301 hasPrimaryLocation W43107923011 @default.
- W4310792301 hasRelatedWork W2731899572 @default.
- W4310792301 hasRelatedWork W2915754718 @default.
- W4310792301 hasRelatedWork W2999805992 @default.
- W4310792301 hasRelatedWork W3091976719 @default.
- W4310792301 hasRelatedWork W3116150086 @default.
- W4310792301 hasRelatedWork W3133861977 @default.
- W4310792301 hasRelatedWork W3200179079 @default.
- W4310792301 hasRelatedWork W4200173597 @default.
- W4310792301 hasRelatedWork W4312417841 @default.
- W4310792301 hasRelatedWork W4321369474 @default.
- W4310792301 hasVolume "105" @default.
- W4310792301 isParatext "false" @default.
- W4310792301 isRetracted "false" @default.
- W4310792301 workType "article" @default.