Results 71 to 80 of about 6,497 (247)
Artificial intelligence for adaptive neuromodulation in drug‐resistant epilepsy
Abstract Drug‐resistant epilepsy (DRE) affects nearly one third of people with epilepsy and is associated with substantial cognitive, psychiatric, and mortality burdens. For patients who are not candidates for resection or laser interstitial thermal therapy, neuromodulation therapies such as vagus nerve stimulation, deep brain stimulation, and ...
Amir Hossein Daraie +10 more
wiley +1 more source
AI‐based localization of the epileptogenic zone using intracranial EEG
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida +5 more
wiley +1 more source
Deep Reinforcement Learning-Based Adversarial Attack and Defense in Industrial Control Systems
Adversarial attacks targeting industrial control systems, such as the Maroochy wastewater system attack and the Stuxnet worm attack, have caused significant damage to related facilities.
Mun-Suk Kim
doaj +1 more source
Workflow of the PV power estimation and ML forecasting methodology. ABSTRACT Accurate prediction of solar panel energy output is vital for managing power systems effectively and maintaining a stable electrical grid. This is especially important in regions that rely heavily on renewable sources. This research provides a direct comparison of five machine
Abdoalateef Alzhrani +4 more
wiley +1 more source
Artificial intelligence and liquidation: Reality, destiny and fantasy
Abstract Artificial intelligence (AI) is increasingly reshaping the administration of corporate liquidation. Beyond its established role in financial prediction and data analytics, AI is now assisting insolvency practitioners in identifying the onset of financial distress, managing creditor communications, tracing and valuing assets and enhancing ...
Kai Zhang, Jingchen Zhao
wiley +1 more source
Benign-salient Region Based End-to-End Adversarial Malware Generation Method [PDF]
Malware detection methods combining visualization techniques and deep learning have gained widespread attention due to their high accuracy and low cost.However,deep learning models are vulnerable to adversarial attacks,where intentional small-scale ...
YUAN Mengjiao, LU Tianliang, HUANG Wanxin, HE Houhan
doaj +1 more source
SURVEY OF ADVERSARIAL ATTACKS AND DEFENSE AGAINST ADVERSARIAL ATTACKS
In recent years, the fields of Artificial Intelligence (AI) and Deep learning (DL) techniques along with Neural Networks (NNs) have shown great progress and scope for future research. Along with all the developments comes the threats and security vulnerabilities to Neural Networks and AI models. A few fabricated inputs/samples can lead to deviations in
Akshat Jain +3 more
openaire +1 more source
The Human Biomarker Navigator integrates the disease continuum, biomarker dynamics, cross‐organ biomarker networks, biomarker classification, and technology‐driven paradigms. It maps how biomarkers link multi‐system physiology and pathology across the nervous, respiratory, endocrine, circulatory, immune, digestive, urinary, reproductive, and ...
Meng‐Yao Li +29 more
wiley +1 more source
Causality adversarial attack generation algorithm for intelligent unmanned communication system
A causality adversarial attack generation algorithm was proposed in response to the causality issue of gradient-based adversarial attack generation algorithms in practical communication system.The sequential input-output features and temporal memory ...
Shuwen YU, Wei XU, Jiacheng YAO
doaj +2 more sources
An adversarial attack method based on pixel location characteristics
Deep learning techniques have been widely used in various fields. However, they face significant security challenges due to the existence of adversarial examples.
Zhao Qin +4 more
doaj +1 more source

