Liu, Qi, Jiang, Han, Liu, Tao, Liu, Zihao, Li, Sicheng, Wen, Wujie, and Shi, Yiyu. Defending Deep Learning-based Biomedical Image Segmentation from Adversarial Attacks: A Low-cost Frequency Refinement Approach. Retrieved from https://par.nsf.gov/biblio/10186304. the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2020 .

Liu, Qi, Jiang, Han, Liu, Tao, Liu, Zihao, Li, Sicheng, Wen, Wujie, & Shi, Yiyu. Defending Deep Learning-based Biomedical Image Segmentation from Adversarial Attacks: A Low-cost Frequency Refinement Approach. the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2020, (). Retrieved from https://par.nsf.gov/biblio/10186304.

Liu, Qi, Jiang, Han, Liu, Tao, Liu, Zihao, Li, Sicheng, Wen, Wujie, and Shi, Yiyu. "Defending Deep Learning-based Biomedical Image Segmentation from Adversarial Attacks: A Low-cost Frequency Refinement Approach". the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2020 (). Country unknown/Code not available. https://par.nsf.gov/biblio/10186304.

@article{osti_10186304,
place = {Country unknown/Code not available}, title = {Defending Deep Learning-based Biomedical Image Segmentation from Adversarial Attacks: A Low-cost Frequency Refinement Approach}, url = {https://par.nsf.gov/biblio/10186304}, abstractNote = {}, journal = {the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2020}, author = {Liu, Qi and Jiang, Han and Liu, Tao and Liu, Zihao and Li, Sicheng and Wen, Wujie and Shi, Yiyu}, }