Results 141 to 150 of about 229,925 (327)

MedVH: Toward Systematic Evaluation of Hallucination for Large Vision Language Models in the Medical Context

Advanced Intelligent Systems, EarlyView.
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, Jiayuan Chen, Fenglin Liu, Changchang Yin, Ping Zhang   +4 more
wiley   +1 more source

Privacy-Adversarial User Representations in Recommender Systems. [PDF]

, 2018
Yehezkel S. Resheff, Yanai Elazar, Moni Shahar, Oren Sar Shalom   +3 more
openalex  

Data-Driven Adversarial Online Control for Unknown Linear Systems [PDF]

, 2023
Zishun Liu, Yongxin Chen
openalex   +1 more source

IAR‐Net: Tabular Deep Learning Model for Interventionalist's Action Recognition

Advanced Intelligent Systems, EarlyView.
This study presents IAR‐Net, a deep‐learning framework for catheterization action recognition. To ensure optimality, this study quantifies interoperator similarities and differences using statistical tests, evaluates the distribution fidelity of synthetic data produced by six generative models, and benchmarks multiple deep‐learning models.
Toluwanimi Akinyemi, Olatunji Omisore, Wenjing Du, Wenke Duan, Chen Bailang, Liu Kun, Lei Wang, Minxin Wei   +7 more
wiley   +1 more source

JND-GAN: Human-Vision-Systems Inspired Generative Adversarial Networks for Image-to-Image Translation

, 2020
Wenbo Zheng, Lan Yan, Chao Gou, Fei‐Yue Wang   +3 more
openalex   +1 more source

A Robot‐Assisted Remote Rehabilitation System for Ankle Fractures Based on Predictive Force and Full‐Cycle Training Strategy

Advanced Intelligent Systems, EarlyView.
This study presents a robot‐assisted remote rehabilitation system for postoperative ankle fractures. The 2.634 kg modular system uses wireless control and deep learning to predict force delays, achieving 100 Hz control (normalized root mean square error ≤ 10.89%).
Zhiyuan He, Peng Chen, Xinye Wang, Yuxiang Chen, Tao Sun   +4 more
wiley   +1 more source

Adversarial system in science [PDF]

Nature, 1994
openaire   +1 more source

Analysis of Nonautonomous Adversarial Systems

, 2018
5 ...
openaire   +2 more sources

Loss‐Based Ensemble Generative Adversarial Network Model for Enhancing the Sperm Morphology Classification

Advanced Intelligent Systems, EarlyView.
A loss‐based ensemble generative adversarial network (GAN) framework is proposed to address mode collapse in sperm morphology classification. By integrating spatial augmentation and multiple GAN models, the study enhances synthetic data quality. The Shifted Window Transformer achieves 95.37% accuracy on the HuSHeM dataset, outperforming previous ...
Berke Cansiz, Hamza Osman Ilhan, Gorkem Serbes   +2 more
wiley   +1 more source

ECGadv: Generating Adversarial Electrocardiogram to Misguide Arrhythmia Classification System [PDF]

, 2019
Huangxun Chen, Chenyu Huang, Qianyi Huang, Qian Zhang, Wei Wang   +4 more
openalex   +1 more source