Results 151 to 160 of about 2,921,969 (298)

RETRACTED: Sankar et al. Utilizing Generative Adversarial Networks for Acne Dataset Generation in Dermatology. BioMedInformatics 2024, 4, 1059–1070

open access: yesBioMedInformatics
The journal retracts the article, “Utilizing Generative Adversarial Networks for Acne Dataset Generation in Dermatology” [...]
Aravinthan Sankar   +5 more
doaj   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

open access: yesAdvanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne   +5 more
wiley   +1 more source

Generating Images Using Generative Adversarial Networks

open access: yes, 2020
U ovom radu su objašnjene neuronske mreže, konvolucijske neuronske mreže i generativne suparničke mreže. Cilj je generiranje slika u boji korištenjem ACGAN-a.
Bartol, Mirko
core  

AI‐Assisted IoT‐Enabled ECG Monitoring: Integrating Foundational and Generative AI Tools for Sustainable Smart Healthcare—Recent Trends

open access: yesAI &Innovation, EarlyView.
ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury   +2 more
wiley   +1 more source

Playing in the Dark: Invisible Chess as a Laboratory for Strategic AI

open access: yesAI &Innovation, EarlyView.
This paper shows that strategic AI evaluated on perfect‐information benchmarks can be brittle in real adversarial settings. By using invisible chess as a benchmark for hidden state and deception, it argues for stricter testing, human oversight, and more cautious governance of high‐stakes AI systems.
Paolo Ciancarini
wiley   +1 more source

Deep learning: Generative adversarial networks and adversarial methods

open access: yes, 2019
Generative adversarial networks (GANs) and other adversarial methods are based on a game-theoretical perspective on joint optimization of two neural networks as players in a game.
Wolterink, Jelmer M.   +7 more
core   +1 more source

Family Dispute Resolution in Australia: The Under‐Servicing of Indigenous, Migrant and Refugee Families Experiencing Family Violence

open access: yesAustralian Journal of Social Issues, EarlyView.
ABSTRACT Improving access to legal services for Indigenous, migrant and refugee women is critical to addressing family violence. In this context, Family Dispute Resolution (FDR) has long been discussed as a solution for separating families. This paper presents key findings of a research evaluation of an Australian Government $8.37 million pilot project
Siobhan McDonnell, Alyson Wright
wiley   +1 more source

Phantom citations: An empirical study of non‐existent and unverifiable references in scholarly literature

open access: yesJournal of the Association for Information Science and Technology, EarlyView.
Abstract The integrity of scholarly communication depends critically on the accuracy and verifiability of cited references. Citations enable readers to trace prior work, assess evidence, and situate new contributions within the existing literature. However, concerns have emerged regarding the presence of references in published papers that cannot be ...
Chengcheng Han   +3 more
wiley   +1 more source

Adversarial Attack Against Images Classification based on Generative Adversarial Networks

open access: yes
Adversarial attacks on image classification systems have always been an important problem in the field of machine learning, and generative adversarial networks (GANs), as popular models in the field of image generation, have been widely used in various ...
Yang, Yahe
core  

An Introduction to Generative Adversarial Networks

open access: yes, 2019
This thesis is a survey of the mathematical theory of Generative Adversarial Networks (GANs).
Paget, Bryan
core   +1 more source

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