Zobrazeno 1 - 10
of 424
pro vyhledávání: '"FAN Yujie"'
Autor:
FAN Yujie, SONG Shengfang, LIU Shichun, CAI Xueqin, LYU Sha, YANG Qiao, DONG Yaoxi, LIAO Juan, LI Hua
Publikováno v:
Di-san junyi daxue xuebao, Vol 43, Iss 14, Pp 1396-1401 (2021)
Objective To explore the value of smart glasses in monitoring the visual behavior of school-age children. Methods A total of 46 myopic children aged 9 to 11 years who visited our hospital during April to August 2019 were included in this study. Quest
Externí odkaz:
https://doaj.org/article/4fe06d8ca11a41acbc8354c18d37b21a
Publikováno v:
Frontiers in Materials, Vol 9 (2022)
Dental health is closely related with people’s quality of life. Teeth are subject to different problems and risks over time. Therefore, studying the influence of age on mechanical properties of tooth enamel is of considerable importance. In this st
Externí odkaz:
https://doaj.org/article/aed3dea7b8ca424fa3f719239a42ad7e
Autor:
Yeh, Chin-Chia Michael, Der, Audrey, Saini, Uday Singh, Lai, Vivian, Zheng, Yan, Wang, Junpeng, Dai, Xin, Zhuang, Zhongfang, Fan, Yujie, Chen, Huiyuan, Aboagye, Prince Osei, Wang, Liang, Zhang, Wei, Keogh, Eamonn
The Matrix Profile (MP), a versatile tool for time series data mining, has been shown effective in time series anomaly detection (TSAD). This paper delves into the problem of anomaly detection in multidimensional time series, a common occurrence in r
Externí odkaz:
http://arxiv.org/abs/2409.09298
Autor:
Wang, Liang, Jain, Shubham, Dou, Yingtong, Wang, Junpeng, Yeh, Chin-Chia Michael, Fan, Yujie, Aboagye, Prince, Zheng, Yan, Dai, Xin, Zhuang, Zhongfang, Saini, Uday Singh, Zhang, Wei
Numerous algorithms have been developed for online product rating prediction, but the specific influence of user and product information in determining the final prediction score remains largely unexplored. Existing research often relies on narrowly
Externí odkaz:
http://arxiv.org/abs/2409.04649
Autor:
Der, Audrey, Yeh, Chin-Chia Michael, Dai, Xin, Chen, Huiyuan, Zheng, Yan, Fan, Yujie, Zhuang, Zhongfang, Lai, Vivian, Wang, Junpeng, Wang, Liang, Zhang, Wei, Keogh, Eamonn
Self-supervised Pretrained Models (PTMs) have demonstrated remarkable performance in computer vision and natural language processing tasks. These successes have prompted researchers to design PTMs for time series data. In our experiments, most self-s
Externí odkaz:
http://arxiv.org/abs/2408.07869
Publikováno v:
Leida xuebao, Vol 9, Iss 1, Pp 143-153 (2020)
In the Synthetic Aperture Radar (SAR) remote sensing imagery of complicated scenes (especially urban scenes), there are a large number of lines and surfaces, such as roads in urban areas and the surfaces of buildings. These microwave-signal-scatteri
Externí odkaz:
https://doaj.org/article/ad0b3c45150e421cb2d0b272ec9c6b84
Autor:
Yeh, Chin-Chia Michael, Fan, Yujie, Dai, Xin, Saini, Uday Singh, Lai, Vivian, Aboagye, Prince Osei, Wang, Junpeng, Chen, Huiyuan, Zheng, Yan, Zhuang, Zhongfang, Wang, Liang, Zhang, Wei
Spatial-temporal forecasting systems play a crucial role in addressing numerous real-world challenges. In this paper, we investigate the potential of addressing spatial-temporal forecasting problems using general time series forecasting models, i.e.,
Externí odkaz:
http://arxiv.org/abs/2402.10487
Autor:
Aboagye, Prince, Zheng, Yan, Wang, Junpeng, Saini, Uday Singh, Dai, Xin, Yeh, Michael, Fan, Yujie, Zhuang, Zhongfang, Jain, Shubham, Wang, Liang, Zhang, Wei
The emergence of pre-trained models has significantly impacted Natural Language Processing (NLP) and Computer Vision to relational datasets. Traditionally, these models are assessed through fine-tuned downstream tasks. However, this raises the questi
Externí odkaz:
http://arxiv.org/abs/2401.02987
Autor:
Yeh, Chin-Chia Michael, Chen, Huiyuan, Fan, Yujie, Dai, Xin, Zheng, Yan, Lai, Vivian, Wang, Junpeng, Zhuang, Zhongfang, Wang, Liang, Zhang, Wei, Keogh, Eamonn
Time series classification is a widely studied problem in the field of time series data mining. Previous research has predominantly focused on scenarios where relevant or foreground subsequences have already been extracted, with each subsequence corr
Externí odkaz:
http://arxiv.org/abs/2311.02561
Autor:
Yeh, Chin-Chia Michael, Chen, Huiyuan, Dai, Xin, Zheng, Yan, Fan, Yujie, Lai, Vivian, Wang, Junpeng, Der, Audrey, Zhuang, Zhongfang, Wang, Liang, Zhang, Wei
Time series data is ubiquitous across various domains such as finance, healthcare, and manufacturing, but their properties can vary significantly depending on the domain they originate from. The ability to perform Content-based Time Series Retrieval
Externí odkaz:
http://arxiv.org/abs/2311.02560