Zobrazeno 1 - 10
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pro vyhledávání: '"Zhang, Haiming"'
Autor:
Zhang, He-Shou, Ponti, Gabriele, Carretti, Ettore, Liu, Ruo-Yu, Morris, Mark R., Haverkorn, Marijke, Locatelli, Nicola, Zheng, Xueying, Aharonian, Felix, Zhang, Haiming, Zhang, Yi, Stel, Giovanni, Strong, Andrew, Yeung, Micheal, Merloni, Andrea
Large-scale magnetic fields are observed off the midplanes of disk galaxies, indicating that they harbour magnetised halos. These halos are crucial to studies of galaxy evolution, galactic-scale outflows, and feedback from star formation activity. Id
Externí odkaz:
http://arxiv.org/abs/2408.06312
Autor:
Si, Haotian, Pei, Changhua, Cui, Hang, Yang, Jingwen, Sun, Yongqian, Zhang, Shenglin, Li, Jingjing, Zhang, Haiming, Han, Jing, Pei, Dan, Li, Jianhui, Xie, Gaogang
Driven by the proliferation of real-world application scenarios and scales, time series anomaly detection (TSAD) has attracted considerable scholarly and industrial interest. However, existing algorithms exhibit a gap in terms of training paradigm, o
Externí odkaz:
http://arxiv.org/abs/2402.10802
Autor:
Wang, Zexin, Pei, Changhua, Ma, Minghua, Wang, Xin, Li, Zhihan, Pei, Dan, Rajmohan, Saravan, Zhang, Dongmei, Lin, Qingwei, Zhang, Haiming, Li, Jianhui, Xie, Gaogang
Time series Anomaly Detection (AD) plays a crucial role for web systems. Various web systems rely on time series data to monitor and identify anomalies in real time, as well as to initiate diagnosis and remediation procedures. Variational Autoencoder
Externí odkaz:
http://arxiv.org/abs/2402.02820
Autor:
Zhang, Haiming, Yan, Xu, Bai, Dongfeng, Gao, Jiantao, Wang, Pan, Liu, Bingbing, Cui, Shuguang, Li, Zhen
3D occupancy prediction is an emerging task that aims to estimate the occupancy states and semantics of 3D scenes using multi-view images. However, image-based scene perception encounters significant challenges in achieving accurate prediction due to
Externí odkaz:
http://arxiv.org/abs/2312.11829
Autor:
Zhang, Haiming, Yuan, Zhihao, Zheng, Chaoda, Yan, Xu, Wang, Baoyuan, Li, Guanbin, Wu, Song, Cui, Shuguang, Li, Zhen
Although existing speech-driven talking face generation methods achieve significant progress, they are far from real-world application due to the avatar-specific training demand and unstable lip movements. To address the above issues, we propose the
Externí odkaz:
http://arxiv.org/abs/2312.07385
Autor:
Liu, Yuhe, Pei, Changhua, Xu, Longlong, Chen, Bohan, Sun, Mingze, Zhang, Zhirui, Sun, Yongqian, Zhang, Shenglin, Wang, Kun, Zhang, Haiming, Li, Jianhui, Xie, Gaogang, Wen, Xidao, Nie, Xiaohui, Ma, Minghua, Pei, Dan
Information Technology (IT) Operations (Ops), particularly Artificial Intelligence for IT Operations (AIOps), is the guarantee for maintaining the orderly and stable operation of existing information systems. According to Gartner's prediction, the us
Externí odkaz:
http://arxiv.org/abs/2310.07637
Autor:
Si, Haotian, Pei, Changhua, Li, Zhihan, Zhao, Yadong, Li, Jingjing, Zhang, Haiming, Diao, Zulong, Li, Jianhui, Xie, Gaogang, Pei, Dan
Massive key performance indicators (KPIs) are monitored as multivariate time series data (MTS) to ensure the reliability of the software applications and service system. Accurately detecting the abnormality of MTS is very critical for subsequent faul
Externí odkaz:
http://arxiv.org/abs/2308.08915
It is widely reported that deep generative models can classify out-of-distribution (OOD) samples as in-distribution with high confidence. In this work, we propose a hypothesis that this phenomenon is due to the reconstruction task, which can cause th
Externí odkaz:
http://arxiv.org/abs/2305.18228
Autor:
Zheng, Chaoda, Yan, Xu, Zhang, Haiming, Wang, Baoyuan, Cheng, Shenghui, Cui, Shuguang, Li, Zhen
3D single object tracking in LiDAR point clouds (LiDAR SOT) plays a crucial role in autonomous driving. Current approaches all follow the Siamese paradigm based on appearance matching. However, LiDAR point clouds are usually textureless and incomplet
Externí odkaz:
http://arxiv.org/abs/2303.12535
Autor:
Zheng, Chaoda, Yan, Xu, Zhang, Haiming, Wang, Baoyuan, Cheng, Shenghui, Cui, Shuguang, Li, Zhen
3D single object tracking (3D SOT) in LiDAR point clouds plays a crucial role in autonomous driving. Current approaches all follow the Siamese paradigm based on appearance matching. However, LiDAR point clouds are usually textureless and incomplete,
Externí odkaz:
http://arxiv.org/abs/2203.01730