Results 91 to 100 of about 804,777 (293)
Adversarial Example Defense via Perturbation Grading Strategy
, 2022 Deep Neural Networks have been widely used in many fields. However, studies have shown that DNNs are easily attacked by adversarial examples, which have tiny perturbations and greatly mislead the correct judgment of DNNs.
Lyu, Wanli +4 more
core +1 more source
Legal Professionals Use an Implicit Checklist to Assess Expert Witness Credibility
Behavioral Sciences &the Law, EarlyView.ABSTRACT In a court of law, some forms of evidence are too technical to interpret without the help of an expert witness. However, expert testimony sometimes leads to wrongful conviction. We used an online survey to quantitatively compare how legal professionals (n = 122) and lay people (n = 109) understood what makes an expert witness credible.
Mahensingh Deonaran +2 more
wiley +1 more source
A divide-and-conquer reconstruction method for defending against adversarial example attacks
Visual IntelligenceIn recent years, defending against adversarial examples has gained significant importance, leading to a growing body of research in this area. Among these studies, pre-processing defense approaches have emerged as a prominent research direction. However,
Xiyao Liu +5 more
doaj +1 more source
Adversarial Attacks and Defense on Texts: A Survey
CoRR, 2020 Deep learning models have been used widely for various purposes in recent years in object recognition, self-driving cars, face recognition, speech recognition, sentiment analysis, and many others. However, in recent years it has been shown that these models possess weakness to noises which force the model to misclassify.
Aminul Huq, Mst. Tasnim Pervin
openaire +2 more sources
Environmental Policy and Governance, EarlyView.ABSTRACT Since the 1990s, environmental policy has shifted toward ecosystem protection and biodiversity conservation, a development often described as an ecological turn. This article argues that in practice this turn has taken the form of an ecological “U‐turn,” as environmental ambitions are subordinated to production‐oriented objectives.
Gisle Andersen +2 more
wiley +1 more source
Scientific ReportsMachine learning (ML) and deep neural networks (DNN) have emerged as powerful tools for enhancing intrusion detection systems (IDS) in cybersecurity.
Zeinab Awad, Magdy Zakaria, Rasha Hassan
doaj +1 more source
The Role of Trade Unions in Environmental Governance: Exploring Workers Legitimacy Judgments
Environmental Policy and Governance, EarlyView.ABSTRACT Trade unions are increasingly expected to play a role in sustainability transitions, but their legitimacy as environmental governance actors remains underexplored. Our study uses a multidimensional framework to examine how workers, both union members and non‐members, evaluate trade union legitimacy “from below.” This framework distinguishes ...
Urša Golob +2 more
wiley +1 more source
Adversarial defenses via vector quantization
NeurocomputingThis is the author-accepted version of our paper published in Neurocomputing.
Zhiyi Dong, Yongyi Mao
openaire +2 more sources
Knowledge sourcing, geopolitics, and FDI: An empirical analysis on the US green and digital sectors
Global Strategy Journal, EarlyView.Abstract Research Summary This paper examines how foreign direct investment (FDI) shapes firms' sourcing of knowledge in the digital and green domains under rising geopolitical frictions. We assemble a firm–country dyadic panel (2013–2020) linking US patent backward citations to firms' FDI, enriched with bilateral geopolitical distance and host‐country
Alberto Maria Radici
wiley +1 more source
Towards adversarial defense with multi-stage information fusion for visual tracking
Engineering Science and Technology, an International JournalIn recent years, the effectiveness and stealth of adversarial attack methods have been continuously improving, posing significant challenges to the robustness and accuracy of visual tracking.
Peng Gao +4 more
doaj +1 more source