Fruit Classification System Using Deep Learning (딥러닝 기반 과일 선별 시스템)

Soo-ho Jeong (정수호); MEONGHUN LEE (이명훈); YOE HYUN (여현)

doi:10.34163/jkits.2018.13.5.009

Fruit Classification System Using Deep Learning

Journal of Knowledge Information Technology and Systems
Abbr : JKITS
2018, 13(5), pp.589-595
DOI : 10.34163/jkits.2018.13.5.009
Publisher : Korea Knowledge Information Technology Society
Research Area : Interdisciplinary Studies > Interdisciplinary Research
Published : October 31, 2018

Soo-ho Jeong ¹, MEONGHUN LEE ², YOE HYUN ¹

¹순천대학교
²국립농업과학원

Accredited

ABSTRACT

Deep learning technology among artificial intelligence technologies has shown good results in image recognition field. In this paper, we use a learning model that is based on a Tensorflow based model that utilizes this deep learning technique and that has been repaired by Inception-v3 model. Based on the characteristics of the fruit, we construct a fruit classification system that classifies into four categories : Healthy apple, Damaged apple, Diseased apple and Discolored apple. To do this, we designed a learning model in which the number of learning iterations was 500 times based on 1,280 apple image data of four kinds and conducted a model evaluation experiment based on the fruit image data taken by the user. Experiments were based on images taken in three directions for accurate model evaluation. Experimental results show that the accuracy of the learning model is more than 90%. However, since fruit showed different classification results according to direction, it suggested the necessity of classification algorithm according to image direction in the future. If such a deep learning based fruit classification system is applied to farmers, fruit quality classifiers due to farm labor shortage are essential, and it will be possible to construct a fruit quality screening system with high accuracy and low cost.

KEYWORDS

Deep learning, Machine learning, Tensorflow, Inception model, Fruit Classification Systems

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* References for papers published after 2023 are currently being built.

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Journal of Knowledge Information Technology and Systems 2023 KCI Impact Factor : 0.89

Fruit Classification System Using Deep Learning

ABSTRACT

KEYWORDS

Citation status

* References for papers published after 2023 are currently being built.

Journal of Knowledge Information Technology and Systems 2023 KCI Impact Factor : 0.89

Fruit Classification System Using Deep Learning

ABSTRACT

KEYWORDS

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REFERENCES (15) * References for papers published after 2023 are currently being built.

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* References for papers published after 2023 are currently being built.