Results 31 to 40 of about 107,198 (316)

A3T: Adversarially Augmented Adversarial Training

CoRR, 2018
accepted for an oral presentation in Machine Deception Workshop, NIPS ...
Akram Erraqabi, Aristide Baratin, Yoshua Bengio, Simon Lacoste-Julien   +3 more
openaire   +2 more sources

Adversarial CAPTCHAs

IEEE Transactions on Cybernetics, 2022
16pages,9 figures ...
Chenghui Shi, Xiaogang Xu 0002, Shouling Ji, Kai Bu, Jianhai Chen, Raheem Beyah, Ting Wang 0006   +6 more
openaire   +3 more sources

Exploring Adversarial Robustness of LiDAR Semantic Segmentation in Autonomous Driving [PDF]

, 2023
Deep learning networks have demonstrated outstanding performance in 2D and 3D vision tasks. However, recent research demonstrated that these networks result in failures when imperceptible perturbations are added to the input known as adversarial attacks.
Perera, Asanka, Asanka Perera, Garratt, Matt, Sreenatha Anavatti, Matt Garratt, Anavatti, Sreenatha, Mahima, K. T. Yasas, K. T. Yasas Mahima   +7 more
core   +1 more source

Aproximaciones legales y jurisprudenciales a la prueba de oficio, en el procedimiento penal adversarial con tendencia acusatoria en el ordenamiento colombiano

Dos Mil Tres Mil, 2017
El presente documento tiene como propósito efectuar una aproximación, desde el punto de vista jurisprudencial y legal, del desarrollo que ha tenido la prueba oficiosa en el sistema penal adversarial de tendencia acusatoria, implementado en Colombia con ...
Jimmy Patiño García, Gabriel Alberto Ospina Herrera, Isabel Indira Molina Ariza   +2 more
doaj   +1 more source

jeromerony/adversarial-library: First release of the library

, 2022
Library containing PyTorch implementations of various adversarial attacks and ...
Jérôme Rony
core   +1 more source

Evolving Robust Policy Coverage Sets in Multi-Objective Markov Decision Processes Through Intrinsically Motivated Self-Play

Frontiers in Neurorobotics, 2018
Many real-world decision-making problems involve multiple conflicting objectives that can not be optimized simultaneously without a compromise. Such problems are known as multi-objective Markov decision processes and they constitute a significant ...
Sherif Abdelfattah, Kathryn Kasmarik, Jiankun Hu   +2 more
doaj   +1 more source

Broadening our understanding of adversarial growth: The contribution of narrative methods

, 2023
After adversity, individuals sometimes report adversarial growth - positive changes in their identity, relationships, and worldviews. We examined how narrative methods enhanced understanding of adversarial growth compared to standard questionnaires ...
Adler, Jonathan M., Jonathan M. Adler (15183883), Nicholas Weststrate (10637012), Laura E. R. Blackie (2735074), Kate C. McLean (8939822), Jonathan M. Adler, Nic M. Weststrate, Kate C. McLean, E. R. Blackie, Laura, Kit Turner (15183878), Kit Turner, Turner, Kit, Laura E. R. Blackie, Weststrate, Nic M., McLean, Kate C.   +14 more
core   +1 more source

sml911/Adversarial-DNN: First Release

, 2020
Cooper graduate research on generative adversaries in adversarial ...
Stephen
core   +1 more source

Targeted Universal Adversarial Examples for Remote Sensing

Remote Sensing, 2022
Researchers are focusing on the vulnerabilities of deep learning models for remote sensing; various attack methods have been proposed, including universal adversarial examples.
Tao Bai, Hao Wang, Bihan Wen
doaj   +1 more source

Adversarial classification [PDF]

Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, 2004
Essentially all data mining algorithms assume that the data-generating process is independent of the data miner's activities. However, in many domains, including spam detection, intrusion detection, fraud detection, surveillance and counter-terrorism, this is far from the case: the data is actively manipulated by an adversary seeking to make the ...
Nilesh N. Dalvi, Pedro M. Domingos, Mausam, Sumit K. Sanghai, Deepak Verma   +4 more
openaire   +1 more source