Chen, Xiaoliang, Li, Baojia, Proietti, Roberto, Zhu, Zuqing, and Yoo, S. J. Self-Taught Anomaly Detection With Hybrid Unsupervised/Supervised Machine Learning in Optical Networks. Retrieved from https://par.nsf.gov/biblio/10105218. Journal of Lightwave Technology 37.7 Web. doi:10.1109/JLT.2019.2902487.

Chen, Xiaoliang, Li, Baojia, Proietti, Roberto, Zhu, Zuqing, & Yoo, S. J. Self-Taught Anomaly Detection With Hybrid Unsupervised/Supervised Machine Learning in Optical Networks. Journal of Lightwave Technology, 37 (7). Retrieved from https://par.nsf.gov/biblio/10105218. https://doi.org/10.1109/JLT.2019.2902487

Chen, Xiaoliang, Li, Baojia, Proietti, Roberto, Zhu, Zuqing, and Yoo, S. J. "Self-Taught Anomaly Detection With Hybrid Unsupervised/Supervised Machine Learning in Optical Networks". Journal of Lightwave Technology 37 (7). Country unknown/Code not available. https://doi.org/10.1109/JLT.2019.2902487. https://par.nsf.gov/biblio/10105218.

@article{osti_10105218,
place = {Country unknown/Code not available}, title = {Self-Taught Anomaly Detection With Hybrid Unsupervised/Supervised Machine Learning in Optical Networks}, url = {https://par.nsf.gov/biblio/10105218}, DOI = {10.1109/JLT.2019.2902487}, abstractNote = {}, journal = {Journal of Lightwave Technology}, volume = {37}, number = {7}, author = {Chen, Xiaoliang and Li, Baojia and Proietti, Roberto and Zhu, Zuqing and Yoo, S. J.}, }