FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4287009358> ?p ?o ?g. }

• W4287009358 endingPage "2197" @default.
• W4287009358 startingPage "2197" @default.
• W4287009358 abstract "Traditional manual garlic root cutting is inefficient and can cause food safety problems. To develop food processing equipment, a novel and accurate object detection method for garlic using deep learning—a convolutional neural network—is proposed in this study. The you-only-look-once (YOLO) algorithm, which is based on lightweight and transfer learning, is the most advanced computer vision method for single large object detection. To detect the bulb, the YOLOv2 model was modified using an inverted residual module and residual structure. The modified model was trained based on images of bulbs with varied brightness, surface attachment, and shape, which enabled sufficient learning of the detector. The optimum minibatches and epochs were obtained by comparing the test results of different training parameters. Research shows that IRM-YOLOv2 is superior to the SqueezeNet, ShuffleNet, and YOLOv2 models of classical neural networks, as well as the YOLOv3 and YOLOv4 algorithm models. The confidence score, average accuracy, deviation, standard deviation, detection time, and storage space of IRM-YOLOv2 were 0.98228, 99.2%, 2.819 pixels, 4.153, 0.0356 s, and 24.2 MB, respectively. In addition, this study provides an important reference for the application of the YOLO algorithm in food research." @default.
• W4287009358 created "2022-07-25" @default.
• W4287009358 creator A5022391443 @default.
• W4287009358 creator A5029393062 @default.
• W4287009358 creator A5029778321 @default.
• W4287009358 creator A5030830722 @default.
• W4287009358 creator A5035085963 @default.
• W4287009358 creator A5066406277 @default.
• W4287009358 creator A5068677405 @default.
• W4287009358 date "2022-07-24" @default.
• W4287009358 modified "2023-09-30" @default.
• W4287009358 title "Convolutional Neural Network for Object Detection in Garlic Root Cutting Equipment" @default.
• W4287009358 cites W1536680647 @default.
• W4287009358 cites W1806891645 @default.
• W4287009358 cites W2063135797 @default.
• W4287009358 cites W2097117768 @default.
• W4287009358 cites W2144506857 @default.
• W4287009358 cites W2570343428 @default.
• W4287009358 cites W2618530766 @default.
• W4287009358 cites W2800584195 @default.
• W4287009358 cites W2884561390 @default.
• W4287009358 cites W2911810010 @default.
• W4287009358 cites W2919115771 @default.
• W4287009358 cites W2921842404 @default.
• W4287009358 cites W2941840259 @default.
• W4287009358 cites W2953618630 @default.
• W4287009358 cites W2963037989 @default.
• W4287009358 cites W2963163009 @default.
• W4287009358 cites W2981927700 @default.
• W4287009358 cites W3003025382 @default.
• W4287009358 cites W3005457696 @default.
• W4287009358 cites W3007890896 @default.
• W4287009358 cites W3013523275 @default.
• W4287009358 cites W3014323018 @default.
• W4287009358 cites W3024743386 @default.
• W4287009358 cites W3033272228 @default.
• W4287009358 cites W3080089353 @default.
• W4287009358 cites W3081253100 @default.
• W4287009358 cites W3092600573 @default.
• W4287009358 cites W3094968069 @default.
• W4287009358 cites W3095317640 @default.
• W4287009358 cites W3105153358 @default.
• W4287009358 cites W3106250896 @default.
• W4287009358 cites W3112383915 @default.
• W4287009358 cites W3117337440 @default.
• W4287009358 cites W3118288473 @default.
• W4287009358 cites W3150234067 @default.
• W4287009358 cites W3155598205 @default.
• W4287009358 cites W3156465006 @default.
• W4287009358 cites W3161307475 @default.
• W4287009358 cites W3168637698 @default.
• W4287009358 cites W3175451967 @default.
• W4287009358 cites W3181037203 @default.
• W4287009358 cites W3204554321 @default.
• W4287009358 cites W3207505510 @default.
• W4287009358 cites W3207764742 @default.
• W4287009358 cites W3214752088 @default.
• W4287009358 cites W4200121270 @default.
• W4287009358 cites W4200615537 @default.
• W4287009358 cites W4207049035 @default.
• W4287009358 cites W4210621772 @default.
• W4287009358 cites W4210659851 @default.
• W4287009358 cites W4210725949 @default.
• W4287009358 cites W4223949485 @default.
• W4287009358 cites W4280590811 @default.
• W4287009358 cites W4281619620 @default.
• W4287009358 cites W4283324405 @default.
• W4287009358 cites W4297797734 @default.
• W4287009358 cites W639708223 @default.
• W4287009358 cites W760861952 @default.
• W4287009358 doi "https://doi.org/10.3390/foods11152197" @default.
• W4287009358 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35892782" @default.
• W4287009358 hasPublicationYear "2022" @default.
• W4287009358 type Work @default.
• W4287009358 citedByCount "2" @default.
• W4287009358 countsByYear W42870093582022 @default.
• W4287009358 countsByYear W42870093582023 @default.
• W4287009358 crossrefType "journal-article" @default.
• W4287009358 hasAuthorship W4287009358A5022391443 @default.
• W4287009358 hasAuthorship W4287009358A5029393062 @default.
• W4287009358 hasAuthorship W4287009358A5029778321 @default.
• W4287009358 hasAuthorship W4287009358A5030830722 @default.
• W4287009358 hasAuthorship W4287009358A5035085963 @default.
• W4287009358 hasAuthorship W4287009358A5066406277 @default.
• W4287009358 hasAuthorship W4287009358A5068677405 @default.
• W4287009358 hasBestOaLocation W42870093581 @default.
• W4287009358 hasConcept C108583219 @default.
• W4287009358 hasConcept C11413529 @default.
• W4287009358 hasConcept C150899416 @default.
• W4287009358 hasConcept C153180895 @default.
• W4287009358 hasConcept C154945302 @default.
• W4287009358 hasConcept C155512373 @default.
• W4287009358 hasConcept C160633673 @default.
• W4287009358 hasConcept C2776151529 @default.
• W4287009358 hasConcept C31972630 @default.
• W4287009358 hasConcept C41008148 @default.
• W4287009358 hasConcept C50644808 @default.
• W4287009358 hasConcept C81363708 @default.

• next