Division of Cow Production Groups Based on SOLOv2 and Improved CNN-LSTM

Guanying Cui, Lulu Qiao, Yuhua Li (), Zhilong Chen, Zhenyu Liang, Chengrui Xin, Maohua Xiao and Xiuguo Zou
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Guanying Cui: College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China
Lulu Qiao: College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China
Yuhua Li: College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China
Zhilong Chen: College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China
Zhenyu Liang: College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China
Chengrui Xin: College of Engineering, Nanjing Agricultural University, Nanjing 210031, China
Maohua Xiao: College of Engineering, Nanjing Agricultural University, Nanjing 210031, China
Xiuguo Zou: College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China

Agriculture, 2023, vol. 13, issue 8, 1-21

Abstract: Udder conformation traits interact with cow milk yield, and it is essential to study the udder characteristics at different levels of production to predict milk yield for managing cows on farms. This study aims to develop an effective method based on instance segmentation and an improved neural network to divide cow production groups according to udders of high- and low-yielding cows. Firstly, the SOLOv2 (Segmenting Objects by LOcations) method was utilized to finely segment the cow udders. Secondly, feature extraction and data processing were conducted to define several cow udder features. Finally, the improved CNN-LSTM (Convolution Neural Network-Long Short-Term Memory) neural network was adopted to classify high- and low-yielding udders. The research compared the improved CNN-LSTM model and the other five classifiers, and the results show that CNN-LSTM achieved an overall accuracy of 96.44%. The proposed method indicates that the SOLOv2 and CNN-LSTM methods combined with analysis of udder traits have the potential for assigning cows to different production groups.

Keywords: cow udder classification; udder features; instance segmentation; CNN-LSTM; udder conformation (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: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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