Laser & Optoelectronics Progress, Volume. 59, Issue 6, 0617026(2022)
Automatic Phase Recognition Method Based on Convolutional Neural Network
[6] Wang F, Wang H, Bian Y M et al. Applications of deep learning in computational imaging[J]. Acta Optica Sinica, 40, 0111002(2020).
[7] Zuo C, Feng S J, Zhang X Y et al. Deep learning based computational imaging: status, challenges, and future[J]. Acta Optica Sinica, 40, 0111003(2020).
[14] Wang P, Liu R, Xin X J et al. Scene classification of optical remote sensing images based on residual networks[J]. Laser & Optoelectronics Progress, 58, 0210001(2021).
[21] Srivastava N, Hinton G, Krizhevsky A et al. Dropout: a simple way to prevent neural networks from overfitting[J]. Journal of Machine Learning Research, 15, 1929-1958(2014).
Get Citation
Copy Citation Text
Ying Ji, Lingran Gong, Shuang Fu, Yawei Wang. Automatic Phase Recognition Method Based on Convolutional Neural Network[J]. Laser & Optoelectronics Progress, 2022, 59(6): 0617026
Category: Medical Optics and Biotechnology
Received: Jun. 28, 2021
Accepted: Aug. 31, 2021
Published Online: Mar. 8, 2022
The Author Email: Ying Ji (jy@ujs.edu.cn)