Ju, H.; Xia, Z.; Yang, J.; Zhou, L.; Dai, B.; Jiao, J.; Wang, D.; Wang, R.
Physics-Informed Weighting Multi-Scale Deep Learning Inversion for Deep-Seated Fault Feature Identification: A Case Study of Aeromagnetic Data in the Dandong Region. Appl. Sci. 2025, 15, 12323.
https://doi.org/10.3390/app152212323
AMA Style
Ju H, Xia Z, Yang J, Zhou L, Dai B, Jiao J, Wang D, Wang R.
Physics-Informed Weighting Multi-Scale Deep Learning Inversion for Deep-Seated Fault Feature Identification: A Case Study of Aeromagnetic Data in the Dandong Region. Applied Sciences. 2025; 15(22):12323.
https://doi.org/10.3390/app152212323
Chicago/Turabian Style
Ju, Haihua, Zhong Xia, Jie Yang, Longran Zhou, Bo Dai, Jian Jiao, Duo Wang, and Runqi Wang.
2025. "Physics-Informed Weighting Multi-Scale Deep Learning Inversion for Deep-Seated Fault Feature Identification: A Case Study of Aeromagnetic Data in the Dandong Region" Applied Sciences 15, no. 22: 12323.
https://doi.org/10.3390/app152212323
APA Style
Ju, H., Xia, Z., Yang, J., Zhou, L., Dai, B., Jiao, J., Wang, D., & Wang, R.
(2025). Physics-Informed Weighting Multi-Scale Deep Learning Inversion for Deep-Seated Fault Feature Identification: A Case Study of Aeromagnetic Data in the Dandong Region. Applied Sciences, 15(22), 12323.
https://doi.org/10.3390/app152212323
