Zobrazeno 1 - 10
of 3 363
pro vyhledávání: '"Chen Yingying"'
Publikováno v:
Kouqiang yixue, Vol 44, Iss 6, Pp 421-425 (2024)
Objective To investigate the labial alveolar bone thickness of maxillary incisors and mesiodistal space in the maxillary adjacent central and lateral incisors based on cone beam computed tomography(CBCT) image data, and provide reference for aestheti
Externí odkaz:
https://doaj.org/article/aa23404b4c014e3792a6619821b407fd
Publikováno v:
Medical Review, Vol 4, Iss 3, Pp 192-206 (2024)
Mammalian lung development starts from a specific cluster of endodermal cells situated within the ventral foregut region. With the orchestrating of delicate choreography of transcription factors, signaling pathways, and cell–cell communications, th
Externí odkaz:
https://doaj.org/article/93ffbe5d622b42ddbb6fdf493abfea4a
Publikováno v:
Shanghai Jiaotong Daxue xuebao. Yixue ban, Vol 43, Iss 11, Pp 1374-1383 (2023)
Objective·To construct an mRNA vaccine encoding hemagglutinin (HA) of influenza A H1N1 virus, and explore the protective effects of different booster vaccination strategies.Methods·Firefly luciferase (Fluc) was used as the reporter gene to construc
Externí odkaz:
https://doaj.org/article/9766a9126405463abdcca8e2a09c8bd1
Autor:
Chen Yingying, Liu Siqi
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
In this paper, we utilize cloud computing to measure the best features in the Rhythmic Gymnastics dataset and compare them to obtain the most relevant feature information. By measuring the degree of uncertainty of random variables and calculating the
Externí odkaz:
https://doaj.org/article/764ec2e6902d4c0d9e60d304bdd7e36b
Publikováno v:
Security and Safety, Vol 3, p 2023025 (2024)
Jamming attacks and unintentional radio interference are some of the most urgent threats harming the dependability of wireless communication and endangering the successful deployment of pervasive applications built on top of wireless networks. Unlike
Externí odkaz:
https://doaj.org/article/d3565eb3ab674e598ffe6542474e55b5
Visual Anomaly Detection (VAD) aims to identify abnormal samples in images that deviate from normal patterns, covering multiple domains, including industrial, logical, and medical fields. Due to the domain gaps between these fields, existing VAD meth
Externí odkaz:
http://arxiv.org/abs/2412.03342
Sequential recommendation approaches have demonstrated remarkable proficiency in modeling user preferences. Nevertheless, they are susceptible to profile pollution attacks (PPA), wherein items are introduced into a user's interaction history delibera
Externí odkaz:
http://arxiv.org/abs/2412.01127
Overfitting has long been stigmatized as detrimental to model performance, especially in the context of anomaly detection. Our work challenges this conventional view by introducing a paradigm shift, recasting overfitting as a controllable and strateg
Externí odkaz:
http://arxiv.org/abs/2412.00560
Autor:
Vu, Tuan-Hung, Valle, Eduardo, Bursuc, Andrei, Kerssies, Tommie, de Geus, Daan, Dubbelman, Gijs, Qian, Long, Zhu, Bingke, Chen, Yingying, Tang, Ming, Wang, Jinqiao, Vojíř, Tomáš, Šochman, Jan, Matas, Jiří, Smith, Michael, Ferrie, Frank, Basu, Shamik, Sakaridis, Christos, Van Gool, Luc
We propose the unified BRAVO challenge to benchmark the reliability of semantic segmentation models under realistic perturbations and unknown out-of-distribution (OOD) scenarios. We define two categories of reliability: (1) semantic reliability, whic
Externí odkaz:
http://arxiv.org/abs/2409.15107
Pretrained vision-language models (VLMs), \eg CLIP, are increasingly used to bridge the gap between open- and close-vocabulary recognition in open-vocabulary image segmentation. As VLMs are generally pretrained with low-resolution images (e.g. $224\t
Externí odkaz:
http://arxiv.org/abs/2408.14776