Classification of Amanita Species Based on Bilinear Networks with Attention Mechanism

Peng Wang, Jiang Liu, Lijia Xu, Peng Huang, Xiong Luo, Yan Hu and Zhiliang Kang
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Peng Wang: College of Mechanical and Electrical Engineering, Sichuan Agricultural University, Ya’an 625000, China
Jiang Liu: College of Mechanical and Electrical Engineering, Sichuan Agricultural University, Ya’an 625000, China
Lijia Xu: College of Mechanical and Electrical Engineering, Sichuan Agricultural University, Ya’an 625000, China
Peng Huang: College of Mechanical and Electrical Engineering, Sichuan Agricultural University, Ya’an 625000, China
Xiong Luo: College of Mechanical and Electrical Engineering, Sichuan Agricultural University, Ya’an 625000, China
Yan Hu: College of Mechanical and Electrical Engineering, Sichuan Agricultural University, Ya’an 625000, China
Zhiliang Kang: College of Mechanical and Electrical Engineering, Sichuan Agricultural University, Ya’an 625000, China

Agriculture, 2021, vol. 11, issue 5, 1-13

Abstract: The accurate classification of Amanita is helpful to its research on biological control and medical value, and it can also prevent mushroom poisoning incidents. In this paper, we constructed the Bilinear convolutional neural networks (B-CNN) with attention mechanism model based on transfer learning to realize the classification of Amanita . When the model is trained, the weight on ImageNet is used for pre-training, and the Adam optimizer is used to update network parameters. In the test process, images of Amanita at different growth stages were used to further test the generalization ability of the model. After comparing our model with other models, the results show that our model greatly reduces the number of parameters while achieving high accuracy (95.2%) and has good generalization ability. It is an efficient classification model, which provides a new option for mushroom classification in areas with limited computing resources.

Keywords: deep learning; bilinear convolutional neural networks; attention mechanism; transfer learning (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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