Laser & Optoelectronics Progress, Volume. 58, Issue 16, 1628002(2021)
Individual Cow Recognition Based on Convolution Neural Network and Transfer Learning
To realize accurate identification of individual cows in a complex farm environment, the SSD (single shot multibox detector) algorithm was improved to solve the problem of poor detection effect for overlapping objects. First, different feature maps were fused to ensure that different feature maps complemented each other and improved the detection effect of overlapping objects. Then, Conv4_3 was removed from the network. The number of candidate frames in other feature maps increased, ensuring the real-time performance of the algorithm and also improving the detection accuracy. Finally, the transfer learning method was used to improve the average accuracy of the algorithm. The experimental results show that compared with the traditional SSD algorithm, the average accuracy (AP) of the improved SSD algorithm is improved by 4.32% in real-time detection, and the AP of the improved SSD algorithm is increased by 3.85% after migration.
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Yongxin Xing, Biqiao Wu, Songping Wu, Tianyi Wang. Individual Cow Recognition Based on Convolution Neural Network and Transfer Learning[J]. Laser & Optoelectronics Progress, 2021, 58(16): 1628002
Category: Remote Sensing and Sensors
Received: Sep. 30, 2020
Accepted: Dec. 8, 2020
Published Online: Aug. 20, 2021
The Author Email: Wang Tianyi (tywang@gzu.edu.cn)