Results 81 to 90 of about 804,833 (294)

Adversarial Example Defense via Perturbation Grading Strategy

open access: yes, 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

open access: yesBehavioral 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

Care and COVID 19: Lessons for liberals and neoliberals

open access: yesChild &Family Social Work, EarlyView., 2023
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

A divide-and-conquer reconstruction method for defending against adversarial example attacks

open access: yesVisual Intelligence
In 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

open access: yesCoRR, 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

The Ecological U‐Turn in Nordic Forestry: Policy Learning, Measurement, and the Retrenchment of Ecological Ambitions

open access: yesEnvironmental 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

An enhanced ensemble defense framework for boosting adversarial robustness of intrusion detection systems

open access: yesScientific Reports
Machine 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

open access: yesEnvironmental 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

open access: yesNeurocomputing
This is the author-accepted version of our paper published in Neurocomputing.
Zhiyi Dong, Yongyi Mao
openaire   +2 more sources

Beyond Prediction: Data, Baselines, Explanation, and Causation in Machine Learning for Food Insecurity

open access: yesFood Safety and Health, EarlyView.
The gains from machine learning in nowcasting and forecasting food insecurity are still small and limited and cannot be observed in all countries. This review summarizes the public resources for data, corrects common misconceptions about model requirements, and establishes baseline requirements, explanations, causal inference, and equity in operational
Shabnam Mehboob   +4 more
wiley   +1 more source

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