Lu, Yantao, Jia, Yunhan, Wang, Jianyu, Li, Bai, Chai, Weiheng, Carin, Lawrence, and Velipasalar, Senem. Enhancing Cross-Task Black-Box Transferability of Adversarial Examples With Dispersion Reduction. Retrieved from https://par.nsf.gov/biblio/10279414. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . Web. doi:10.1109/CVPR42600.2020.00102.

Lu, Yantao, Jia, Yunhan, Wang, Jianyu, Li, Bai, Chai, Weiheng, Carin, Lawrence, & Velipasalar, Senem. Enhancing Cross-Task Black-Box Transferability of Adversarial Examples With Dispersion Reduction. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), (). Retrieved from https://par.nsf.gov/biblio/10279414. https://doi.org/10.1109/CVPR42600.2020.00102

Lu, Yantao, Jia, Yunhan, Wang, Jianyu, Li, Bai, Chai, Weiheng, Carin, Lawrence, and Velipasalar, Senem. "Enhancing Cross-Task Black-Box Transferability of Adversarial Examples With Dispersion Reduction". 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (). Country unknown/Code not available. https://doi.org/10.1109/CVPR42600.2020.00102. https://par.nsf.gov/biblio/10279414.

@article{osti_10279414,
place = {Country unknown/Code not available}, title = {Enhancing Cross-Task Black-Box Transferability of Adversarial Examples With Dispersion Reduction}, url = {https://par.nsf.gov/biblio/10279414}, DOI = {10.1109/CVPR42600.2020.00102}, abstractNote = {}, journal = {2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, author = {Lu, Yantao and Jia, Yunhan and Wang, Jianyu and Li, Bai and Chai, Weiheng and Carin, Lawrence and Velipasalar, Senem}, editor = {null} }