Zheng, L.; Yang, T.; Liu, W.; Lai, Y.; Yang, J.
Enhancing Accuracy of Flame Equivalence Ratio Measurements: An Attention-Based Convolutional Neural Network Approach for Overcoming Limitations in Traditional Color Modeling. Sensors 2024, 24, 6853.
https://doi.org/10.3390/s24216853
AMA Style
Zheng L, Yang T, Liu W, Lai Y, Yang J.
Enhancing Accuracy of Flame Equivalence Ratio Measurements: An Attention-Based Convolutional Neural Network Approach for Overcoming Limitations in Traditional Color Modeling. Sensors. 2024; 24(21):6853.
https://doi.org/10.3390/s24216853
Chicago/Turabian Style
Zheng, Lukai, Tiantian Yang, Wenjia Liu, Yufeng Lai, and Jiansheng Yang.
2024. "Enhancing Accuracy of Flame Equivalence Ratio Measurements: An Attention-Based Convolutional Neural Network Approach for Overcoming Limitations in Traditional Color Modeling" Sensors 24, no. 21: 6853.
https://doi.org/10.3390/s24216853
APA Style
Zheng, L., Yang, T., Liu, W., Lai, Y., & Yang, J.
(2024). Enhancing Accuracy of Flame Equivalence Ratio Measurements: An Attention-Based Convolutional Neural Network Approach for Overcoming Limitations in Traditional Color Modeling. Sensors, 24(21), 6853.
https://doi.org/10.3390/s24216853
