中国科学院机构知识库网格系统: 检索

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	Spatial-Temporal Graph Network for Video Crowd Counting 期刊论文 OAI收割 IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2023, 卷号: 33, 期号: 1, 页码: 228-241 作者: Wu, Zhe; Zhang, Xinfeng; Tian, Geng; Wang, Yaowei; Huang, Qingming \| 收藏 \| 浏览/下载：9/0 \| 提交时间：2023/07/12 Computational modeling Predictive models Analytical models Long short term memory Optical flow Integrated circuit modeling Head Video-based crowd counting spatiotemporal graph attention multi-scale module
	Discovering the Graph-Based Flow Patterns of Car Tourists Using License Plate Data: A Case Study in Shenzhen, China 期刊论文 OAI收割 JOURNAL OF ADVANCED TRANSPORTATION, 2020, 卷号: 2020, 页码: 4795830 作者: He Bing; Kong Bo; Yin Ling; Wu Qin; Hu Jinxing \| 收藏 \| 浏览/下载：40/0 \| 提交时间：2020/09/25 Graph-Based Flow
	A video synthesis method for flow patterns (EI CONFERENCE) 会议论文 OAI收割 2010 2nd IEEE International Conference on Network Infrastructure and Digital Content, IC-NIDC 2010, September 24, 2010 - September 26, 2010, Beijing, China 作者: Chen J.; Liu J.; Yu D.; Yu D.; Li J. 收藏 \| 浏览/下载：24/0 \| 提交时间：2013/03/25 This paper presents a new video synthesis method for flow patterns. We can use it to synthesize video of natural phenomena that exhibit continuous flow patterns. It is based on flow-based video synthesis algorithm and combines partial ideas of graph cuts algorithm. This algorithm can process input videos of natural phenomena of flow patterns (e.g. rivers flames and waterfalls) and synthesize more realistic and active seamless video of arbitrary length than other algorithms. It is simple to implement. The results show that our method can produce satisfactory effects based on user inputs. 2010 IEEE.