Paper
9 August 2023 Research on the improved apple classification method of AlexNet
Huifang Yang, Weihua Wang, Zhicheng Mao
Author Affiliations +
Proceedings Volume 12782, Third International Conference on Image Processing and Intelligent Control (IPIC 2023); 127821I (2023) https://doi.org/10.1117/12.3000778
Event: Third International Conference on Image Processing and Intelligent Control (IPIC 2023), 2023, Kuala Lumpur, Malaysia
Abstract
To address the issue of high cost and low efficiency in the manual sorting of apples, we proposed an improved apple classification method based on the AlexNet architecture. The algorithm added a batch normalization layer after each convolutional layer in the network structure to speed up the model's training process. Furthermore, we replaced the fully connected layer with a global average pooling layer to reduce the number of training parameters and save model training time. To improve the algorithm's robustness, we also performed data augmentation on the training samples before validating the algorithm to obtain an expanded dataset. Experimental results showed that the improved AlexNet network shortened the training time by 0.54%, increased the testing speed by 2.5%, and improved the accuracy by 1.12% compared to the original AlexNet network. Moreover, the training time of the improved AlexNet network was lower than that of other networks (AlexNet, ResNet50, Vgg16). The improved AlexNet network can efficiently and quickly classify apples and promote the automation of apple classification.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Huifang Yang, Weihua Wang, and Zhicheng Mao "Research on the improved apple classification method of AlexNet", Proc. SPIE 12782, Third International Conference on Image Processing and Intelligent Control (IPIC 2023), 127821I (9 August 2023); https://doi.org/10.1117/12.3000778
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KEYWORDS
Education and training

Data modeling

RGB color model

Batch normalization

Overfitting

Convolutional neural networks

Statistical modeling

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