Apple automatic classification method based on improved VGG11

Jianxia Wang; Hongjiao Zhang; Wanzhen Zhou

doi:10.1117/12.2684183

1 August 2023 Apple automatic classification method based on improved VGG11

Jianxia Wang, Hongjiao Zhang, Wanzhen Zhou

Proceedings Volume 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023); 127541W (2023) https://doi.org/10.1117/12.2684183
Event: 2023 3rd International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 2023, Hangzhou, China

Abstract

In order to solve the problem that traditional fruit grading methods are easy to cause damage to fruits and low grading accuracy, taking apple grading as an example, transfer learning is used to pre-train the data-enhanced dataset, and an adaptive pooling layer is added to the feature layer of the original VGG11 model, and then an SE module based on attention mechanism is added between the adaptive pooling layer and the classifier layer to increase the weight of the effective feature map and reduce the weight of the invalid or small feature map. In order to make the training model get better results, thereby improving the accuracy of the algorithm. Comparing the improved model with GoogleNet model, LeNet-5 model, etc., the SE-VGG11 model has the best effect, the classification accuracy can reach 98.53%, and an apple grading time only takes 0.1s, which can meet the needs of factory automation classification. In summary, the improved model can be used for efficient grading of apples.

Citation Download Citation

Jianxia Wang, Hongjiao Zhang, and Wanzhen Zhou "Apple automatic classification method based on improved VGG11", Proc. SPIE 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 127541W (1 August 2023); https://doi.org/10.1117/12.2684183

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available