Results 81 to 90 of about 804,777 (293)
Care and COVID 19: Lessons for liberals and neoliberals
Abstract Within the liberal political traditions, care is regarded as a private matter, a problem of ethics rather than justice. Social justice is framed as an issue of economics (re/distribution), culture (recognition) and/or politics (representation).
Kathleen Lynch
wiley +1 more source
MAD: Meta Adversarial Defense Benchmark
Adversarial training (AT) is a prominent technique employed by deep learning models to defend against adversarial attacks, and to some extent, enhance model robustness.
Peng, X. +4 more
core
ABSTRACT In an era of rising geopolitical tensions and environmental instability, corporate political activities have become increasingly intertwined with ethical challenges and sustainability requirements. This study investigates the influence of environmental dynamics and corporate ethical responsibility on interorganizational conflict and ...
David Yulong Liu +4 more
wiley +1 more source
Stylized Pairing for Robust Adversarial Defense
Recent studies show that deep neural networks (DNNs)-based object recognition algorithms overly rely on object textures rather than global object shapes, and DNNs are also vulnerable to human-less perceptible adversarial perturbations. Based on these two
Xiao Liu, Wentao Zhao, Dejian Guan
core +1 more source
A Unified Framework for Adversarial Attack and Defense in Constrained Feature Space [PDF]
The generation of feasible adversarial examples is necessary for properly assessing models that work in constrained feature space. However, it remains a challenging task to enforce constraints into attacks that were designed for computer vision.
Simonetto, Thibault +11 more
core +1 more source
Beyond the Adversarial Rivalry: A Developmental Rights‐Based Model for Minor‐on‐Minor Crime, Part 1
ABSTRACT When children harm children, the conventional victim–perpetrator framework is ill‐equipped to address the developmental, relational, and institutional complexities involved. While juvenile justice scholarship increasingly emphasizes rehabilitation, and victims' rights literature has advanced child‐sensitive protection, minor‐on‐minor offending
Tali Gal, Ruthy Lowenstein Lazar
wiley +1 more source
Exploring Synergy of Denoising and Distillation: Novel Method for Efficient Adversarial Defense
Escalating advancements in artificial intelligence (AI) has prompted significant security concerns, especially with its increasing commercialization. This necessitates research on safety measures to securely utilize AI models.
Inpyo Hong, Sokjoon Lee
doaj +1 more source
Beyond the Adversarial Rivalry: A Developmental Rights‐Based Model for Minor‐on‐Minor Crime, Part 2
ABSTRACT When children harm children, the conventional victim–perpetrator framework is ill‐equipped to address the developmental, relational, and institutional complexities involved. While juvenile justice scholarship increasingly emphasizes rehabilitation, and victims' rights literature has advanced child‐sensitive protections, minor‐on‐minor ...
Tali Gal, Ruthy Lowenstein Lazar
wiley +1 more source
Adversarial defense based on distribution transfer
The presence of adversarial examples poses a significant threat to deep learning models and their applications. Existing defense methods provide certain resilience against adversarial examples, but often suffer from decreased accuracy and generalization ...
Chen, Jiahao, Dong, Li, Yan, Diqun
core
Generative Adversarial Trainer: Defense to Adversarial Perturbations with GAN
We propose a novel technique to make neural network robust to adversarial examples using a generative adversarial network. We alternately train both classifier and generator networks. The generator network generates an adversarial perturbation that can easily fool the classifier network by using a gradient of each image.
Hyeungill Lee +2 more
openaire +2 more sources

