Zobrazeno 1 - 10
of 667
pro vyhledávání: '"Chen Yi-Ping Phoebe"'
Point tracking is a challenging task in computer vision, aiming to establish point-wise correspondence across long video sequences. Recent advancements have primarily focused on temporal modeling techniques to improve local feature similarity, often
Externí odkaz:
http://arxiv.org/abs/2407.20730
Autor:
Zheng, Yu, Koh, Huan Yee, Jin, Ming, Chi, Lianhua, Wang, Haishuai, Phan, Khoa T., Chen, Yi-Ping Phoebe, Pan, Shirui, Xiang, Wei
The detection of anomalies in multivariate time series data is crucial for various practical applications, including smart power grids, traffic flow forecasting, and industrial process control. However, real-world time series data is usually not well
Externí odkaz:
http://arxiv.org/abs/2401.05800
Autor:
Zheng, Yu, Koh, Huan Yee, Jin, Ming, Chi, Lianhua, Phan, Khoa T., Pan, Shirui, Chen, Yi-Ping Phoebe, Xiang, Wei
Multivariate time-series anomaly detection is critically important in many applications, including retail, transportation, power grid, and water treatment plants. Existing approaches for this problem mostly employ either statistical models which cann
Externí odkaz:
http://arxiv.org/abs/2307.08390
Transformer framework has been showing superior performances in visual object tracking for its great strength in information aggregation across the template and search image with the well-known attention mechanism. Most recent advances focus on explo
Externí odkaz:
http://arxiv.org/abs/2301.10938
Real-world data typically follow a long-tailed distribution, where a few majority categories occupy most of the data while most minority categories contain a limited number of samples. Classification models minimizing cross-entropy struggle to repres
Externí odkaz:
http://arxiv.org/abs/2207.09052
Recently vision transformer models have become prominent models for a range of vision tasks. These models, however, are usually opaque with weak feature interpretability. Moreover, there is no method currently built for an intrinsically interpretable
Externí odkaz:
http://arxiv.org/abs/2207.05358
Transformer architecture has been showing its great strength in visual object tracking, for its effective attention mechanism. Existing transformer-based approaches adopt the pixel-to-pixel attention strategy on flattened image features and unavoidab
Externí odkaz:
http://arxiv.org/abs/2205.03806
Anomaly detection from graph data is an important data mining task in many applications such as social networks, finance, and e-commerce. Existing efforts in graph anomaly detection typically only consider the information in a single scale (view), th
Externí odkaz:
http://arxiv.org/abs/2202.05525
Autor:
Chen Yi-Ping Phoebe, Bork Peer
Publikováno v:
BMC Genomics, Vol 13, Iss Suppl 1, p I1 (2012)
Externí odkaz:
https://doaj.org/article/c092501c26054353b5bbb55b55fd9105
Autor:
Aldawsari, Saja, Chen, Yi-Ping Phoebe
Publikováno v:
In Computer Science Review November 2024 54