A lightweight residual neural network for apple external quality grading

Xiaojie Sun; Jian Qin; Long Yan; Xiaojia Liu

doi:10.1117/12.2660018

3 February 2023 A lightweight residual neural network for apple external quality grading

Xiaojie Sun, Jian Qin, Long Yan, Xiaojia Liu

Proceedings Volume 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022); 1251138 (2023) https://doi.org/10.1117/12.2660018
Event: Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 2022, Hulun Buir, China

Abstract

The current problem of relatively backward and inefficient apple fruit grading technology, computer vision-based classification methods are widely adopted, but traditional visual classification networks face the problems of many parameters, high computational effort and unsatisfactory classification accuracy. Therefore, this paper proposes a lightweight residual network-based apple external quality grading method. Firstly, based on the traditional residual neural network, the network uses group convolution to replace the standard convolution in the original residual units， the aims are to reduce the number of model parameters and computational effort; Secondly, to address the information non-circulation problem between group channels caused by group convolution, a Channel Shuffle operation is used to mix inter-group features to improve model performance; Finally, a parallel pooling structure is proposed to solve the problem of information loss of traditional pooling features. To build a dataset of apple images with extensive coverage of external quality information, and to perform data enhancement on a limited dataset, and to conduct experiments based on the augmented dataset using improved models in comparison with common neural network models. The experimental results show that the improved lightweight residual network model has only 2.97M parameters, the FLOPs are only 1/5 of the traditional model, and the classification accuracy is 96.5%, which is helpful for future implementation of apple grading in low performance mobile terminals.

Citation Download Citation

Xiaojie Sun, Jian Qin, Long Yan, and Xiaojia Liu "A lightweight residual neural network for apple external quality grading", Proc. SPIE 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 1251138 (3 February 2023); https://doi.org/10.1117/12.2660018

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KEYWORDS

Convolution

Performance modeling

Neural networks

Instrument modeling

Data modeling

Mobile devices

Feature extraction

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