Using a region-based convolutional neural network (R-CNN) for potato segmentation in a sorting process

Jaka Verk (Avtor), Jernej Hernavs (Avtor), Simon Klančnik (Avtor)

Povzetek

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.

Ključne besede

segmentacija slike;sortiranje krompirja;nevronske mreže;maska RCNN;odkrivanje predmetov;proizvodni procesi;strojno učenje;umetna inteligenca;image segmentation;potato sorting;neural network;mask RCNN;object detection;production process;machine learning;AI;

Podatki

Jezik:	Angleški jezik
Leto izida:	2025
Tipologija:	1.01 - Izvirni znanstveni članek
Organizacija:	UM FS - Fakulteta za strojništvo
Založnik:	MDPI
UDK:	681.5:004.8
COBISS:	230214403
ISSN:	2304-8158
Št. ogledov:	0
Št. prenosov:	9
Ocena:	0 (0 glasov)
Metapodatki:

Ostali podatki

Sekundarni jezik:	Slovenski jezik
Sekundarne ključne besede:	segmentacija slike;sortiranje krompirja;nevronske mreže;maska RCNN;odkrivanje predmetov;proizvodni procesi;strojno učenje;umetna inteligenca;
Vrsta dela (COBISS):	Članek v reviji
Strani:	18 str.
Letnik:	ǂVol. ǂ14
Zvezek:	ǂiss. ǂ7, [article no.] 1131
Čas izdaje:	March 2025
DOI:	10.3390/foods14071131
ID:	26119011