FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4290052392> ?p ?o ?g. }

• W4290052392 endingPage "107268" @default.
• W4290052392 startingPage "107268" @default.
• W4290052392 abstract "Accurate identification of the veraison process is essential for improving wine quality, which is challenging due to the variability of veraison among berries of the same cluster in algorihtm design, and also the subjective and labor-intensive issues in mannual identification. Therefore, this study proposed a method combining deep learning and image analysis to identify veraison in colored wine grapes under natural field growing conditions. The removal of irrelevant background was first achieved by semantic segmentation model, and then Mask R-CNN instance segmentation pipeline was constructed with anchor parameters optimization. In particular, three kinds of backbone networks were analyzed and compared in Mask R-CNN, and the overall performance of ResNet50-FPN was the best, with the testset Average Precision reaching 81.53% and the inference time being only 45.70 ms/frame. Then, a method for characterizing berry veraison by H component of HSV color space was proposed and the invariance of the H component of three colored wine grape berries under different light conditions was verified and discussed. An algorithm was developed to identify veraison progress by calculating the percentage of the number of berries of different grades in the total number of berries of the whole grape bunches. The test accuracy reached 92.50%, 91.25% and 91.88% for three wine grapes including Cabernet Sauvignon, Matheran and Syrah respectively. The proposed method is able to provide vital reference for automated monitoring and intelligent management decisions of grape growth." @default.
• W4290052392 created "2022-08-06" @default.
• W4290052392 creator A5001081849 @default.
• W4290052392 creator A5027658278 @default.
• W4290052392 creator A5032437498 @default.
• W4290052392 creator A5047505143 @default.
• W4290052392 creator A5066330538 @default.
• W4290052392 creator A5070955749 @default.
• W4290052392 creator A5073334385 @default.
• W4290052392 creator A5077696885 @default.
• W4290052392 date "2022-09-01" @default.
• W4290052392 modified "2023-10-16" @default.
• W4290052392 title "Identifying veraison process of colored wine grapes in field conditions combining deep learning and image analysis" @default.
• W4290052392 cites W1594793571 @default.
• W4290052392 cites W1955857676 @default.
• W4290052392 cites W1987284380 @default.
• W4290052392 cites W2005230415 @default.
• W4290052392 cites W2019168270 @default.
• W4290052392 cites W2019829222 @default.
• W4290052392 cites W2054081978 @default.
• W4290052392 cites W2064640776 @default.
• W4290052392 cites W2110764733 @default.
• W4290052392 cites W2136159141 @default.
• W4290052392 cites W2145654276 @default.
• W4290052392 cites W2533752934 @default.
• W4290052392 cites W2552149001 @default.
• W4290052392 cites W2606438808 @default.
• W4290052392 cites W2768010570 @default.
• W4290052392 cites W2896971046 @default.
• W4290052392 cites W2909501706 @default.
• W4290052392 cites W2941099341 @default.
• W4290052392 cites W2945440006 @default.
• W4290052392 cites W2963150697 @default.
• W4290052392 cites W2963743382 @default.
• W4290052392 cites W2981708487 @default.
• W4290052392 cites W2999278897 @default.
• W4290052392 cites W3004977026 @default.
• W4290052392 cites W3020289656 @default.
• W4290052392 cites W3037597928 @default.
• W4290052392 cites W3039712305 @default.
• W4290052392 cites W3082872030 @default.
• W4290052392 cites W3116690419 @default.
• W4290052392 cites W3137102587 @default.
• W4290052392 cites W4221010126 @default.
• W4290052392 cites W639708223 @default.
• W4290052392 doi "https://doi.org/10.1016/j.compag.2022.107268" @default.
• W4290052392 hasPublicationYear "2022" @default.
• W4290052392 type Work @default.
• W4290052392 citedByCount "8" @default.
• W4290052392 countsByYear W42900523922022 @default.
• W4290052392 countsByYear W42900523922023 @default.
• W4290052392 crossrefType "journal-article" @default.
• W4290052392 hasAuthorship W4290052392A5001081849 @default.
• W4290052392 hasAuthorship W4290052392A5027658278 @default.
• W4290052392 hasAuthorship W4290052392A5032437498 @default.
• W4290052392 hasAuthorship W4290052392A5047505143 @default.
• W4290052392 hasAuthorship W4290052392A5066330538 @default.
• W4290052392 hasAuthorship W4290052392A5070955749 @default.
• W4290052392 hasAuthorship W4290052392A5073334385 @default.
• W4290052392 hasAuthorship W4290052392A5077696885 @default.
• W4290052392 hasConcept C144027150 @default.
• W4290052392 hasConcept C148518694 @default.
• W4290052392 hasConcept C154945302 @default.
• W4290052392 hasConcept C185592680 @default.
• W4290052392 hasConcept C2776034682 @default.
• W4290052392 hasConcept C2994243853 @default.
• W4290052392 hasConcept C31903555 @default.
• W4290052392 hasConcept C33923547 @default.
• W4290052392 hasConcept C41008148 @default.
• W4290052392 hasConcept C55952523 @default.
• W4290052392 hasConcept C86803240 @default.
• W4290052392 hasConcept C89600930 @default.
• W4290052392 hasConceptScore W4290052392C144027150 @default.
• W4290052392 hasConceptScore W4290052392C148518694 @default.
• W4290052392 hasConceptScore W4290052392C154945302 @default.
• W4290052392 hasConceptScore W4290052392C185592680 @default.
• W4290052392 hasConceptScore W4290052392C2776034682 @default.
• W4290052392 hasConceptScore W4290052392C2994243853 @default.
• W4290052392 hasConceptScore W4290052392C31903555 @default.
• W4290052392 hasConceptScore W4290052392C33923547 @default.
• W4290052392 hasConceptScore W4290052392C41008148 @default.
• W4290052392 hasConceptScore W4290052392C55952523 @default.
• W4290052392 hasConceptScore W4290052392C86803240 @default.
• W4290052392 hasConceptScore W4290052392C89600930 @default.
• W4290052392 hasLocation W42900523921 @default.
• W4290052392 hasOpenAccess W4290052392 @default.
• W4290052392 hasPrimaryLocation W42900523921 @default.
• W4290052392 hasRelatedWork W1968654649 @default.
• W4290052392 hasRelatedWork W2054081978 @default.
• W4290052392 hasRelatedWork W2508513449 @default.
• W4290052392 hasRelatedWork W2521846692 @default.
• W4290052392 hasRelatedWork W2782847524 @default.
• W4290052392 hasRelatedWork W2998927625 @default.
• W4290052392 hasRelatedWork W3123965542 @default.
• W4290052392 hasRelatedWork W4225641102 @default.
• W4290052392 hasRelatedWork W4290052392 @default.
• W4290052392 hasRelatedWork W4310448121 @default.
• W4290052392 hasVolume "200" @default.

• next