期刊文献+

Activation Function: Cell Recognition Based on YoLov5s/m 被引量:2

Activation Function: Cell Recognition Based on YoLov5s/m
下载PDF
导出
摘要 Activation functions play a critical role in neural networks. The paper mainly studies activation functions with four activation functions that were the selection for reference and comparison. The Mish activation function was expending as the Mish_PLUS activation function, the Sigmoid activation function, and the Tanh were combined to obtain a new Sigmoid_Tanh activation function. We used the recently popular YoLov5s and YoLov5m as the basic structure of the neural network. The function realized in this article was the recognition function of red blood cells, white blood cells, and platelets. Through the role and comparison of different activation functions in the neural network structure, the test results show that, in this paper, the training precision curve under the Sigmoid_Tanh activation function was better than that under the action of other activation functions. That means that the accuracy of cell recognition under the activation function was higher. Activation functions play a critical role in neural networks. The paper mainly studies activation functions with four activation functions that were the selection for reference and comparison. The Mish activation function was expending as the Mish_PLUS activation function, the Sigmoid activation function, and the Tanh were combined to obtain a new Sigmoid_Tanh activation function. We used the recently popular YoLov5s and YoLov5m as the basic structure of the neural network. The function realized in this article was the recognition function of red blood cells, white blood cells, and platelets. Through the role and comparison of different activation functions in the neural network structure, the test results show that, in this paper, the training precision curve under the Sigmoid_Tanh activation function was better than that under the action of other activation functions. That means that the accuracy of cell recognition under the activation function was higher.
作者 Zuomin Yang Zuomin Yang(College of Electromechanical Engineering, Qingdao University of Science and Technology, Qingdao, China)
出处 《Journal of Computer and Communications》 2021年第12期1-16,共16页 电脑和通信(英文)
关键词 Mish_PLUS Sigmoid_Tanh Cell Recognition Mish_PLUS Sigmoid_Tanh Cell Recognition
  • 相关文献

同被引文献26

引证文献2

二级引证文献3

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部