Mango Classification System Uses Image Processing Technology and Artificial Intelligence

Thong, Nguyen Duc; Thinh, Nguyen Truong; Cong, Huynh Thanh

doi:10.1109/icsse.2019.8823119

Cited by 7 publications

(2 citation statements)

References 4 publications

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“…Several researchers have proposed various methods to build classification models [4,6,8,10]. For example, Image processing techniques and artificial intelligence (AI) have been applied to analyze, evaluate and classify the fruit, the image captured by the imaging system.…”

Section: Related Workmentioning

confidence: 99%

“…The classification system helps customers to determine the kind of fruit. Finally, who created many classification systems, most of the classifications use color, size, volume [8], and shape [9] and use different methods to classify fruit type. One of the biggest challenges in developing fruit detection and recognition systems is the slight difference in the image [10].…”

Section: Introductionmentioning

confidence: 99%

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Shallots Classification using CNN

Wathan

2022

ijicom

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Shallots are an essential plant for the commercial and home industries included in the Allium genus. Choosing the type of onion based on the characteristics is very easy for humans to do but not easy for humans to do in the spice industry; therefore, machines will replace human limitations in recognizing the type of shallots in the spice industry. Inspired by the success of research on the classification of shallots using SVM, we propose CNN to tackle the problem of classifying types of shallots based on shape and texture features. This study uses the CNN method's performance to categorize different varieties of shallots based on their shape and texture features. In a shallot classification test, our approach promises higher accuracy and lower loss than standard machine techniques.

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Section: Related Workmentioning

confidence: 99%