Tangelo grading method based on deep neural network and fuzzy decision

Keqiong Chen; Jiaming Wang; Litao Fu; Chengxi Zhao; Yu Xie; Weitao Li

doi:10.1117/12.3025933

8 April 2024 Tangelo grading method based on deep neural network and fuzzy decision

Keqiong Chen, Jiaming Wang, Litao Fu, Chengxi Zhao, Yu Xie, Weitao Li

Proceedings Volume 13090, International Conference on Computer Application and Information Security (ICCAIS 2023); 130901E (2024) https://doi.org/10.1117/12.3025933
Event: International Conference on Computer Application and Information Security (ICCAIS 2023), 2023, Wuhan, China

Abstract

To address the problem that a single discriminant index is difficult to comprehensively evaluate the quality of tangelo, this paper explores a tangelo grading method based on deep neural network and fuzzy decision. Firstly, a tangelo grading model based on deep neural network and fuzzy decision was constructed, and its structure and functional characteristics were given; Secondly, based on Standard Normal Variate (SNV) and Principal Component Analysis (PCA), the spectral space construction mechanism of tangelo dry water defect characteristics is given. Then, a deep neural network model of dry water defect grade of tangelo is constructed; Thirdly, the Soluble Solids Content (SSC) feature spectral space extraction model based on Multivariate Scattering Correction (MSC) and PCA was constructed. A deep neural network regression model for SSC content of tangelo was constructed; Finally, based on fuzzy logic, a fusion decision classifier for tangelo grading was constructed. The experimental results show that the proposed method can realize the comprehensive decision of tangelo quality and effectively improve the utilization rate of fruit.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Keqiong Chen, Jiaming Wang, Litao Fu, Chengxi Zhao, Yu Xie, and Weitao Li "Tangelo grading method based on deep neural network and fuzzy decision", Proc. SPIE 13090, International Conference on Computer Application and Information Security (ICCAIS 2023), 130901E (8 April 2024); https://doi.org/10.1117/12.3025933

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KEYWORDS

Education and training

Fuzzy logic

Neural networks

Feature extraction

Principal component analysis

Convolution

Data modeling

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