Zobrazeno 1 - 10
of 346
pro vyhledávání: '"YAN, Zhenyu"'
In image editing tasks, high-quality text editing capabilities can significantly reduce human and material resource costs. Current methods rely heavily on training data based on OCR text segment detection, where the text is tightly aligned with the m
Externí odkaz:
http://arxiv.org/abs/2410.09879
Anomaly detection is a critical task in industrial manufacturing, aiming to identify defective parts of products. Most industrial anomaly detection methods assume the availability of sufficient normal data for training. This assumption may not hold t
Externí odkaz:
http://arxiv.org/abs/2408.01960
Autor:
Yang, Bufang, Jiang, Siyang, Xu, Lilin, Liu, Kaiwei, Li, Hai, Xing, Guoliang, Chen, Hongkai, Jiang, Xiaofan, Yan, Zhenyu
Large language models (LLMs) have the potential to transform digital healthcare, as evidenced by recent advances in LLM-based virtual doctors. However, current approaches rely on patient's subjective descriptions of symptoms, causing increased misdia
Externí odkaz:
http://arxiv.org/abs/2405.12541
Autor:
Shi, Shuyao, Ling, Neiwen, Jiang, Zhehao, Huang, Xuan, He, Yuze, Zhao, Xiaoguang, Yang, Bufang, Bian, Chen, Xia, Jingfei, Yan, Zhenyu, Yeung, Raymond, Xing, Guoliang
Recently,smart roadside infrastructure (SRI) has demonstrated the potential of achieving fully autonomous driving systems. To explore the potential of infrastructure-assisted autonomous driving, this paper presents the design and deployment of Soar,
Externí odkaz:
http://arxiv.org/abs/2404.13786
Individuals with visual impairments, encompassing both partial and total difficulties in visual perception, are referred to as visually impaired (VI) people. An estimated 2.2 billion individuals worldwide are affected by visual impairments. Recent ad
Externí odkaz:
http://arxiv.org/abs/2404.02508
Autor:
Yang, Bufang, He, Lixing, Ling, Neiwen, Yan, Zhenyu, Xing, Guoliang, Shuai, Xian, Ren, Xiaozhe, Jiang, Xin
Deep Learning (DL) models have been widely deployed on IoT devices with the help of advancements in DL algorithms and chips. However, the limited resources of edge devices make these on-device DL models hard to be generalizable to diverse environment
Externí odkaz:
http://arxiv.org/abs/2311.10986
Autor:
Ouyang, Xiaomin, Shuai, Xian, Li, Yang, Pan, Li, Zhang, Xifan, Fu, Heming, Cheng, Sitong, Wang, Xinyan, Cao, Shihua, Xin, Jiang, Mok, Hazel, Yan, Zhenyu, Yu, Doris Sau Fung, Kwok, Timothy, Xing, Guoliang
Alzheimer's Disease (AD) and related dementia are a growing global health challenge due to the aging population. In this paper, we present ADMarker, the first end-to-end system that integrates multi-modal sensors and new federated learning algorithms
Externí odkaz:
http://arxiv.org/abs/2310.15301
Autor:
Yang, Jun, Zhao, Xiao-Hong, Yan, Zhenyu, Wang, Xiangyu I., Zhang, Yan-Qiu, An, Zheng-Hua, Cai, Ce, Li, Xin-Qiao, Li, Zihan, Liu, Jia-Cong, Liu, Zi-Ke, Ma, Xiang, Meng, Yan-Zhi, Peng, Wen-Xi, Qiao, Rui, Shao, Lang, Song, Li-Ming, Tan, Wen-Jun, Wang, Ping, Wang, Chen-Wei, Wen, Xiang-Yang, Xiao, Shuo, Xue, Wang-Chen, Yang, Yu-han, Yin, Yihan, Zhang, Bing, Zhang, Fan, Zhang, Shuai, Zhang, Shuang-Nan, Zheng, Chao, Zheng, Shi-Jie, Xiong, Shao-Lin, Zhang, Bin-Bin
Publikováno v:
ApJL 947 L11 (2023)
The brightest Gamma-ray burst, GRB 221009A, has spurred numerous theoretical investigations, with particular attention paid to the origins of ultra-high energy TeV photons during the prompt phase. However, analyzing the mechanism of radiation of phot
Externí odkaz:
http://arxiv.org/abs/2303.00898
Indoor self-localization is a highly demanded system function for smartphones. The current solutions based on inertial, radio frequency, and geomagnetic sensing may have degraded performance when their limiting factors take effect. In this paper, we
Externí odkaz:
http://arxiv.org/abs/2210.08493
Adversarial example attack endangers the mobile edge systems such as vehicles and drones that adopt deep neural networks for visual sensing. This paper presents {\em Sardino}, an active and dynamic defense approach that renews the inference ensemble
Externí odkaz:
http://arxiv.org/abs/2204.08189