Apple Fruit Edge Detection Model Using a Rough Set and Convolutional Neural Network
Apple Fruit Edge Detection Model Using a Rough Set and Convolutional Neural Network
About this item
Full title
Author / Creator
Li, Junqing , Han, Ruiyi , Li, Fangyi , Dong, Guoao , Ma, Yu , Yang, Wei , Qi, Guanghui and Zhang, Liang
Publisher
Switzerland: MDPI AG
Journal title
Language
English
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Publication information
Publisher
Switzerland: MDPI AG
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Scope and Contents
Contents
Accurately and effectively detecting the growth position and contour size of apple fruits is crucial for achieving intelligent picking and yield predictions. Thus, an effective fruit edge detection algorithm is necessary. In this study, a fusion edge detection model (RED) based on a convolutional neural network and rough sets was proposed. The Fast...
Alternative Titles
Full title
Apple Fruit Edge Detection Model Using a Rough Set and Convolutional Neural Network
Authors, Artists and Contributors
Author / Creator
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_2db248cbd3ef4ec8882038776a58407d
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_2db248cbd3ef4ec8882038776a58407d
Other Identifiers
ISSN
1424-8220
E-ISSN
1424-8220
DOI
10.3390/s24072283
