Meat freshness recognition based on improved ResNet34 model

Haoren Liao; Ling Chen

doi:10.1117/12.2681030

23 May 2023 Meat freshness recognition based on improved ResNet34 model

Haoren Liao, Ling Chen

Proceedings Volume 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023); 126452Q (2023) https://doi.org/10.1117/12.2681030
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 2023, Hangzhou, China

Abstract

Meat freshness is an important index to measure the quality of meat, but currently, the commonly used methods of rapid inspection require specific equipment as well as the environment, and it is difficult for ordinary consumers to distinguish meat freshness quickly and accurately by using these methods. To address this problem this paper proposes a ResNet34 network based on ResNet34 network and adding channel attention mechanism to build a SE- ReseNet34 network model for meat freshness recognition is constructed, and the training method of transfer learning is used to accelerate the convergence of the model. Compared with ResNet34, MobileNetV2, DenseNet121, and ResNext50 network models, the accuracy of the model test set is improved by 1.4%, 2.5%, 0.7%, and 1.6%, respectively. The test set accuracy can reach 99.6% while having high accuracy and recall, and the results show that this is an efficient and fast method for identifying meat freshness with some practical significance.

Citation Download Citation

Haoren Liao and Ling Chen "Meat freshness recognition based on improved ResNet34 model", Proc. SPIE 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 126452Q (23 May 2023); https://doi.org/10.1117/12.2681030

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