Wang, Hong, Xie, Yunchao, Li, Dawei, Deng, Heng, Zhao, Yunxin, Xin, Ming, and Lin, Jian. Rapid Identification of X-ray Diffraction Patterns Based on Very Limited Data by Interpretable Convolutional Neural Networks. Retrieved from https://par.nsf.gov/biblio/10195859. Journal of Chemical Information and Modeling 60.4 Web. doi:10.1021/acs.jcim.0c00020.

Wang, Hong, Xie, Yunchao, Li, Dawei, Deng, Heng, Zhao, Yunxin, Xin, Ming, & Lin, Jian. Rapid Identification of X-ray Diffraction Patterns Based on Very Limited Data by Interpretable Convolutional Neural Networks. Journal of Chemical Information and Modeling, 60 (4). Retrieved from https://par.nsf.gov/biblio/10195859. https://doi.org/10.1021/acs.jcim.0c00020

Wang, Hong, Xie, Yunchao, Li, Dawei, Deng, Heng, Zhao, Yunxin, Xin, Ming, and Lin, Jian. "Rapid Identification of X-ray Diffraction Patterns Based on Very Limited Data by Interpretable Convolutional Neural Networks". Journal of Chemical Information and Modeling 60 (4). Country unknown/Code not available. https://doi.org/10.1021/acs.jcim.0c00020. https://par.nsf.gov/biblio/10195859.

@article{osti_10195859,
place = {Country unknown/Code not available}, title = {Rapid Identification of X-ray Diffraction Patterns Based on Very Limited Data by Interpretable Convolutional Neural Networks}, url = {https://par.nsf.gov/biblio/10195859}, DOI = {10.1021/acs.jcim.0c00020}, abstractNote = {}, journal = {Journal of Chemical Information and Modeling}, volume = {60}, number = {4}, author = {Wang, Hong and Xie, Yunchao and Li, Dawei and Deng, Heng and Zhao, Yunxin and Xin, Ming and Lin, Jian}, }