Zobrazeno 1 - 10
of 2 231
pro vyhledávání: '"Yang Zhiwei"'
Publikováno v:
Youqi dizhi yu caishoulu, Vol 31, Iss 5, Pp 153-161 (2024)
Underground natural gas storage is an essential infrastructure for strategic reserves， emergency peak shaving， and national energy security. It is also one of the directions for optimizing the industrial layout of mature oilfields and promoting g
Externí odkaz:
https://doaj.org/article/cf7ec13e401a470fae92f6b5c8a8cab9
Publikováno v:
Redai dili, Vol 41, Iss 2, Pp 315-326 (2021)
The urban-rural transition zone has obvious characteristics such as urban expansion transition, dynamic spatial structure, and a diversified human environment. It is of great significance to study the spatial interaction intensity between urban and r
Externí odkaz:
https://doaj.org/article/18670344bf14417293e1469a2b101a40
Autor:
Wu, Peng, Zhou, Xuerong, Pang, Guansong, Yang, Zhiwei, Yan, Qingsen, Wang, Peng, Zhang, Yanning
Current weakly supervised video anomaly detection (WSVAD) task aims to achieve frame-level anomalous event detection with only coarse video-level annotations available. Existing works typically involve extracting global features from full-resolution
Externí odkaz:
http://arxiv.org/abs/2408.05905
Autor:
Yang, Zhiwei, Wei, Yuecen, Li, Haoran, Li, Qian, Jiang, Lei, Sun, Li, Yu, Xiaoyan, Hu, Chunming, Peng, Hao
Social event detection refers to extracting relevant message clusters from social media data streams to represent specific events in the real world. Social event detection is important in numerous areas, such as opinion analysis, social safety, and d
Externí odkaz:
http://arxiv.org/abs/2407.18274
Most fake news detection methods learn latent feature representations based on neural networks, which makes them black boxes to classify a piece of news without giving any justification. Existing explainable systems generate veracity justifications f
Externí odkaz:
http://arxiv.org/abs/2405.03371
Weakly supervised video anomaly detection (WSVAD) is a challenging task. Generating fine-grained pseudo-labels based on weak-label and then self-training a classifier is currently a promising solution. However, since the existing methods use only RGB
Externí odkaz:
http://arxiv.org/abs/2404.08531
Weakly supervised semantic segmentation (WSSS) with image-level labels intends to achieve dense tasks without laborious annotations. However, due to the ambiguous contexts and fuzzy regions, the performance of WSSS, especially the stages of generatin
Externí odkaz:
http://arxiv.org/abs/2404.08195
Weakly supervised semantic segmentation (WSSS) with image-level labels aims to achieve segmentation tasks without dense annotations. However, attributed to the frequent coupling of co-occurring objects and the limited supervision from image-level lab
Externí odkaz:
http://arxiv.org/abs/2402.18467
Noise pollution is a persistent environmental concern with severe implications for human health and resources. Acoustic metamaterials offer the potential for ultrathin devices with exceptional sound control capabilities. However, most lack practical
Externí odkaz:
http://arxiv.org/abs/2402.08597
High-quality whole-slide scanning is expensive, complex, and time-consuming, thus limiting the acquisition and utilization of high-resolution histopathology images in daily clinical work. Deep learning-based single-image super-resolution (SISR) techn
Externí odkaz:
http://arxiv.org/abs/2401.15613