| Title: | Using a region-based convolutional neural network (R-CNN) for potato segmentation in a sorting process |
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| Authors: | ID Verk, Jaka (Author)
ID Hernavs, Jernej (Author)
ID Klančnik, Simon (Author) |
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| Files: |  foods-14-01131.pdf (5,97 MB)
MD5: 46F9AD2A65FE8B86873768A5EC3B79A8
 https://www.mdpi.com/2304-8158/14/7/1131
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FS - Faculty of Mechanical Engineering
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| Abstract: | This study focuses on the segmentation part in the development of a potato-sorting system that utilizes camera input for the segmentation and classification of potatoes. The key challenge addressed is the need for efficient segmentation to allow the sorter to handle a higher volume of potatoes simultaneously. To achieve this, the study employs a region-based convolutional neural network (R-CNN) approach for the segmentation task, while trying to achieve more precise segmentation than with classic CNN-based object detectors. Specifically, Mask R-CNN is implemented and evaluated based on its performance with different parameters in order to achieve the best segmentation results. The implementation and methodologies used are thoroughly detailed in this work. The findings reveal that Mask R-CNN models can be utilized in the production process of potato sorting and can improve the process. |
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| Keywords: | image segmentation, potato sorting, neural network, mask RCNN, object detection, production process, machine learning, AI |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 27.02.2025 |
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| Article acceptance date: | 24.03.2025 |
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| Publication date: | 25.03.2025 |
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| Publisher: | MDPI |
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| Year of publishing: | 2025 |
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| Number of pages: | 18 str. |
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| Numbering: | Vol. 14, iss. 7, [article no.] 1131 |
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| PID: | 20.500.12556/DKUM-92296  |
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| UDC: | 681.5:004.8 |
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| ISSN on article: | 2304-8158 |
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| COBISS.SI-ID: | 230214403 |
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| DOI: | 10.3390/foods14071131 |
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| Copyright: | © 2025 by the authors |
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| Publication date in DKUM: | 27.03.2025 |
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| Views: | 203 |
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| Downloads: | 38 |
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| Metadata: |    |
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| Categories: | Misc.
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