Zobrazeno 1 - 10
of 6 277
pro vyhledávání: '"Lu Chun"'
Autor:
Hong Wei, Hongjun Huang, Haoqiang He, Yuanming Xiao, Lu Chun, Zhiqiang Jin, Hanyang Li, Li Zheng, Jinmin Zhao, Zainen Qin
Publikováno v:
Research, Vol 7 (2024)
Externí odkaz:
https://doaj.org/article/e7f3b86589e941d2941e498ee79159df
Autor:
Hong Wei, Hongjun Huang, Haoqiang He, Yuanming Xiao, Lu Chun, Zhiqiang Jin, Hanyang Li, Li Zheng, Jinmin Zhao, Zainen Qin
Publikováno v:
Research, Vol 7 (2024)
The activation of pro-inflammatory M1-type macrophages by overexpression of reactive oxygen species (ROS) and reactive nitrogen species (RONS) in synovial membranes contributes to osteoarthritis (OA) progression and cartilage matrix degradation. Here
Externí odkaz:
https://doaj.org/article/25d693484da941a4bcfe104effd56ddd
Publikováno v:
Jisuanji kexue, Vol 49, Iss 11, Pp 228-233 (2022)
The traditional reinforced concrete detection method uses linear fitting or standard value look-up table method,which can only roughly estimate the diameter of rebar.In view of the fact that there are few sample data of the diameter detection,and the
Externí odkaz:
https://doaj.org/article/093acc2f6e584c918af39b1082a554e8
Publikováno v:
Shipin yu jixie, Vol 39, Iss 5, Pp 55-63,100 (2023)
Objective: This study aimed to investigate the residues and risk assessment of pesticides in peach gum. Methods: The quantitative analysis of 44 pesticide residues in peach gum was established based on liquid chromatography tandem-mass spectrometry
Externí odkaz:
https://doaj.org/article/fbc40538eab04653bc91ae217651912c
Autor:
Li, Jonathan Weiping, Liang, Ren-Wei, Yeh, Cheng-Han, Tsai, Cheng-Chang, Yu, Kuanchun, Lu, Chun-Shien, Chen, Shang-Tse
This paper examines the phenomenon of probabilistic robustness overestimation in TRADES, a prominent adversarial training method. Our study reveals that TRADES sometimes yields disproportionately high PGD validation accuracy compared to the AutoAttac
Externí odkaz:
http://arxiv.org/abs/2410.07675
In recent years, Vision-Language Models (VLMs) have demonstrated significant advancements in artificial intelligence, transforming tasks across various domains. Despite their capabilities, these models are susceptible to jailbreak attacks, which can
Externí odkaz:
http://arxiv.org/abs/2410.01438
Visual State Space Model (VSS) has demonstrated remarkable performance in various computer vision tasks. However, in the process of development, backdoor attacks have brought severe challenges to security. Such attacks cause an infected model to pred
Externí odkaz:
http://arxiv.org/abs/2408.11679
Amid the proliferation of forged images, notably the tsunami of deepfake content, extensive research has been conducted on using artificial intelligence (AI) to identify forged content in the face of continuing advancements in counterfeiting technolo
Externí odkaz:
http://arxiv.org/abs/2407.18614
Deep learning technology has brought convenience and advanced developments but has become untrustworthy because of its sensitivity to inconspicuous perturbations (i.e., adversarial attacks). Attackers may utilize this sensitivity to manipulate predic
Externí odkaz:
http://arxiv.org/abs/2407.15524
Semi-supervised learning (SSL) has achieved remarkable performance with a small fraction of labeled data by leveraging vast amounts of unlabeled data from the Internet. However, this large pool of untrusted data is extremely vulnerable to data poison
Externí odkaz:
http://arxiv.org/abs/2407.10180