Results 81 to 90 of about 4,416 (262)

Artificial intelligence and liquidation: Reality, destiny and fantasy

International Insolvency Review, EarlyView.
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

Adversarial defenses via vector quantization

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

Human biomarker navigator

iMeta, EarlyView.
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, Qian Zhang, Zijie Wang, Zeping Gui, Jing Liu, Jingda Li, Maojun Jiang, Zukang Chang, Qingqing Han, Bendong Yang, Tariq Saeed, Jun Li, Jinghan Jia, Chenghu Song, Tong Shao, Tianhuan Peng, Xueying Zhang, Pingping Guo, Jun Luo, Gangao Yang, Yuan Wan, Gokhan Zengin, Quan Yuan, Lingru Li, Xiaohui Fan, Yang Luo, Lvyun Zhu, Yanfei Zheng, Wenjun Mao, Wenlong Sun   +29 more
wiley   +1 more source

Towards adversarial defense with multi-stage information fusion for visual tracking

Engineering Science and Technology, an International Journal
In recent years, the effectiveness and stealth of adversarial attack methods have been continuously improving, posing significant challenges to the robustness and accuracy of visual tracking.
Peng Gao, Wen-Jia Tang, Long Xu, Fei Wang, Ru-Yue Yuan   +4 more
doaj   +1 more source

On Adaptive Attacks to Adversarial Example Defenses

CoRR, 2020
Adaptive attacks have (rightfully) become the de facto standard for evaluating defenses to adversarial examples. We find, however, that typical adaptive evaluations are incomplete. We demonstrate that thirteen defenses recently published at ICLR, ICML and NeurIPS---and chosen for illustrative and pedagogical purposes---can be circumvented despite ...
Florian Tramèr, Nicholas Carlini, Wieland Brendel, Aleksander Madry   +3 more
openaire   +3 more sources

Preparing for Tomorrow's Teamwork: Insights From eSports on How Human Expertise Shapes Training Needs for AI‐Integrated Work

Journal of Organizational Behavior, EarlyView.
ABSTRACT As organizations increasingly adopt human‐AI teams (HATs), understanding how to enhance team performance is paramount. A crucially underexplored area for supporting HATs is training, particularly helping human teammates to work with these inorganic counterparts.
Caitlin M. Lancaster, Christopher Flathmann, Jennifer Hsu, Nathan J. McNeese, Thomas A. O'Neill, Eduardo Salas   +5 more
wiley   +1 more source

A knowledge distillation strategy for enhancing the adversarial robustness of lightweight automatic modulation classification models

IET Communications
Automatic modulation classification models based on deep learning models are at risk of being interfered by adversarial attacks. In an adversarial attack, the attacker causes the classification model to misclassify the received signal by adding carefully
Fanghao Xu, Chao Wang, Jiakai Liang, Chenyang Zuo, Keqiang Yue, Wenjun Li   +5 more
doaj   +1 more source

Harnessing Aggregation‐Induced Emission for Advanced Disease Diagnosis: Mechanisms, Strategies and Future Perspectives

Medicine Bulletin, EarlyView.
The figure was created in BioRender.com. ABSTRACT Accurate and early diagnosis remains a key challenge in modern disease management. Conventional diagnostic methods often suffer from limitations in sensitivity, spatial resolution, and practical usability.
Zizhuo Du, Li Song, Xingrui Chen, Jun Jing, Yingchen Wang, Yue Jiang, Jiahui Gao, Dan Li, Feiran Xie, Peihong Xiao, Ben Zhong Tang   +10 more
wiley   +1 more source

Multi‐Agent Reinforcement Learning for Joint Police Patrol and Dispatch

Naval Research Logistics (NRL), EarlyView.
ABSTRACT Police patrol units need to split their time between performing preventive patrol and being dispatched to serve emergency incidents. In the existing literature, patrol and dispatch decisions are often studied separately. We consider joint optimization of these two decisions to improve police operations efficiency and reduce response time to ...
Matthew Repasky, He Wang, Yao Xie
wiley   +1 more source

PuVAE: A Variational Autoencoder to Purify Adversarial Examples

IEEE Access, 2019
Deep neural networks are widely used and exhibit excellent performance in many areas. However, they are vulnerable to adversarial attacks that compromise networks at inference time by applying elaborately designed perturbations to input data.
Uiwon Hwang, Jaewoo Park, Hyemi Jang, Sungroh Yoon, Nam Ik Cho   +4 more
doaj   +1 more source