Adversarial diversity and hard positive generation A Rozsa, EM Rudd, TE Boult Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 164 | 2016 |
Moon: A mixed objective optimization network for the recognition of facial attributes EM Rudd, M Günther, TE Boult European Conference on Computer Vision, 19-35, 2016 | 144 | 2016 |
The extreme value machine EM Rudd, LP Jain, WJ Scheirer, TE Boult IEEE transactions on pattern analysis and machine intelligence 40 (3), 762-768, 2017 | 102 | 2017 |
A survey of stealth malware attacks, mitigation measures, and steps toward autonomous open world solutions EM Rudd, A Rozsa, M Günther, TE Boult IEEE Communications Surveys & Tutorials 19 (2), 1145-1172, 2016 | 89 | 2016 |
Toward open-set face recognition M Gunther, S Cruz, EM Rudd, TE Boult Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 45 | 2017 |
Are facial attributes adversarially robust? A Rozsa, M Günther, EM Rudd, TE Boult 2016 23rd International Conference on Pattern Recognition (ICPR), 3121-3127, 2016 | 36 | 2016 |
Facial attributes: Accuracy and adversarial robustness A Rozsa, M Günther, EM Rudd, TE Boult Pattern Recognition Letters 124, 100-108, 2019 | 31 | 2019 |
Exemplar codes for facial attributes and tattoo recognition MJ Wilber, E Rudd, B Heflin, YM Lui, TE Boult IEEE Winter Conference on Applications of Computer Vision, 205-212, 2014 | 20 | 2014 |
Meade: Towards a malicious email attachment detection engine EM Rudd, R Harang, J Saxe 2018 IEEE International Symposium on Technologies for Homeland Security (HST …, 2018 | 15 | 2018 |
PARAPH: presentation attack rejection by analyzing polarization hypotheses EM Rudd, M Gunther, TE Boult Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 14 | 2016 |
Incremental open set intrusion recognition using extreme value machine J Henrydoss, S Cruz, EM Rudd, M Gunther, TE Boult 2017 16th IEEE International Conference on Machine Learning and Applications …, 2017 | 12 | 2017 |
Automated big security text pruning and classification K Alzhrani, EM Rudd, CE Chow, TE Boult 2016 IEEE International Conference on Big Data (Big Data), 3629-3637, 2016 | 12 | 2016 |
Automated big text security classification K Alzhrani, EM Rudd, TE Boult, CE Chow 2016 IEEE Conference on Intelligence and Security Informatics (ISI), 103-108, 2016 | 12 | 2016 |
Open set intrusion recognition for fine-grained attack categorization S Cruz, C Coleman, EM Rudd, TE Boult 2017 IEEE International Symposium on Technologies for Homeland Security (HST …, 2017 | 9 | 2017 |
Automated us diplomatic cables security classification: Topic model pruning vs. classification based on clusters K Alzhrani, EM Rudd, CE Chow, TE Boult 2017 IEEE International Symposium on Technologies for Homeland Security (HST …, 2017 | 9 | 2017 |
{ALOHA}: Auxiliary Loss Optimization for Hypothesis Augmentation EM Rudd, FN Ducau, C Wild, K Berlin, R Harang 28th {USENIX} Security Symposium ({USENIX} Security 19), 303-320, 2019 | 6 | 2019 |
Towards principled uncertainty estimation for deep neural networks R Harang, EM Rudd arXiv preprint arXiv:1810.12278, 2018 | 5 | 2018 |
Learning from Context: Exploiting and Interpreting File Path Information for Better Malware Detection A Kyadige, EM Rudd, K Berlin arXiv preprint arXiv:1905.06987, 2019 | 3 | 2019 |
Gesture-based user identity verification as an open set problem for smartphones K Tornai, WJ Scheirer 2019 International Conference on Biometrics (ICB), 1-8, 2019 | 2 | 2019 |
Automatic Malware Description via Attribute Tagging and Similarity Embedding FN Ducau, EM Rudd, TM Heppner, A Long, K Berlin arXiv preprint arXiv:1905.06262, 2019 | 2 | 2019 |