Results 131 to 140 of about 221,728 (275)
ECGadv: Generating Adversarial Electrocardiogram to Misguide Arrhythmia Classification System
Huangxun Chen +4 more
openalex +2 more sources
Adversarial attack on deep learning-based dermatoscopic image recognition systems
Jérôme Allyn +4 more
openalex +1 more source
Implementation of generative adversarial networks in HPCC systems using GNN bundle
Ambu Karthik +3 more
openalex +2 more sources
On‐Device Brain Tumor Classification from MR Images Using Smartphone
Herein, various deep learning models are trained for brain tumor classification task, and model performances are compared. The performance is further improved by using the proposed preprocessing algorithm before training. The MobileViT model, which is the best‐performing model in terms of balance between inference time and success rate, is integrated ...
Halil Ibrahim Ustun +3 more
wiley +1 more source
An incremental adversarial training method enables timeliness and rapid new knowledge acquisition. [PDF]
Ge Y, Dong Y, Sun H, Liu Y, Wang C.
europepmc +1 more source
Automated Detection System for Adversarial Examples with High-Frequency Noises Sieve
Dang Duy Thang, Toshihiro Matsui
openalex +2 more sources
This study addresses multiagent defense challenges against low‐cost swarm attacks through a hierarchical framework combining resource allocation and PPO optimization. The three‐layer architecture coordinates strategic planning, deployment optimization, and real‐time execution.
Xiaokai Fei +2 more
wiley +1 more source
AI-driven cybersecurity framework for anomaly detection in power systems. [PDF]
V M V +4 more
europepmc +1 more source
MedVH introduces the first comprehensive benchmark for diagnosing hallucinations in medical vision‐language models. Across six multitask evaluations, eight state‐of‐the‐art LVLMs reveal that domain‐tuned models, while strong on routine questions, hallucinate more than general models, raising serious concerns for real‐world clinical use.
Zishan Gu +4 more
wiley +1 more source

