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Start Over Author "Long, Ying" Publisher springer international publishing
50 results on '"Long, Ying"'

11. Cities in Transition

Author

Long, Ying, Zhang, Enjia, Lozano, Rodrigo, Series Editor, Carpenter, Angela, Series Editor, Long, Ying, and Zhang, Enjia

Published
2021
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12. Revealing the Spatial Preferences Embedded in Online Activities: A Case Study of Chengdu, China

Author

Zhang, Enjia, Ye, Yu, Hou, Jingxuan, Long, Ying, Angelidou, Margarita, Editorial Board Member, Farnaz Arefian, Fatemeh, Editorial Board Member, Batty, Michael, Editorial Board Member, Davoudi, Simin, Editorial Board Member, DeVerteuil, Geoffrey, Editorial Board Member, Jones, Paul, Editorial Board Member, Kirby, Andrew, Editorial Board Member, Kropf, Karl, Editorial Board Member, Lucas, Karen, Editorial Board Member, Maretto, Marco, Editorial Board Member, Modarres, Ali, Editorial Board Member, Neuhaus, Fabian, Editorial Board Member, Nijhuis, Steffen, Editorial Board Member, Aráujo de Oliveira, Vitor Manuel, Editorial Board Member, Silver, Christopher, Editorial Board Member, Strappa, Giuseppe, Editorial Board Member, Vojnovic, Igor, Editorial Board Member, Whitehand, Jeremy W. R., Editorial Board Member, Yamu, Claudia, Editorial Board Member, Geertman, S. C. M., editor, Pettit, Christopher, editor, Goodspeed, Robert, editor, and Staffans, Aija, editor

Published
2021
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44. Anomaly Detection of Single Sensors Using OCSVM_KNN

Author

Su, Jing, Long, Ying, Qiu, Xiaofeng, Li, Shufang, Liu, Daowei, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Wang, Yu, editor, Xiong, Hui, editor, Argamon, Shlomo, editor, Li, XiangYang, editor, and Li, JianZhong, editor

Published
2015
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49. The Performance Evaluation for the Efficiency of Coastal Regional Innovation Network Based on DEA

Author

Song Cheng, Yuan Haiyan, and Hu Long-ying

Subjects
ComputingMilieux_GENERAL, Index system, Order (exchange), Principal component analysis, ComputerApplications_COMPUTERSINOTHERSYSTEMS, Business, Environmental economics, China, Analysis method
Abstract

In order to evaluate the innovation efficiency of China’s coastal regional innovation network accurately, this paper selects 11 coastal provinces, municipalities and autonomous regions, and simplifies the published financial data by the factor analysis method and the principal component analysis method. We build the innovation efficiency of China’s coastal regional innovation network evaluation index system from the interaction between scientific research institutions and symbiotic environment, the interaction between enterprises and symbiotic environment and the interaction between scientific research institutions and enterprises. This paper analyzes the innovation efficiency of China’s coastal regional innovation network evaluation and gives the input-output DEA model. It gives the coastal regional innovation network evaluation results also.

Published
2018

50. Multi-cue Based Multi-target Tracking with Boosted MHT

Author

Tianzhu Zhang, Shengsheng Qian, Changsheng Xu, and Long Ying

Subjects
Boosting (machine learning), Computer science, business.industry, Multiple hypotheses, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Optical flow, Video content analysis, Pattern recognition, Virtual reality, Discriminative model, Data association, Multi target tracking, Computer vision, Artificial intelligence, business
Abstract

Tracking multiple objects is critical to automatic video content analysis and virtual reality. The major problem is how to solve data association problem when ambiguous observations are caused by objects in close proximity or occlusion. To tackle this problem, we propose a boosted multiple hypotheses tracking (BMHT) algorithm for multiobject tracking. Here, on-line boosting learning is adopted to enhance the discriminative property and enlarge search space of the generative tracker MHT. To make the tracker be more reliable, a multi-cue integration strategy is adopted to consider different kinds of features under the on-line boosting framework. In this paper, we integrate both appearance and motion pattern information. For simplicity, Haar-like features and optical flow are adopted. We test our BMHT tracker on several challenging video sequences that involve heavy occlusion and pose variations. Experimental results show that the proposed BMHT achieves good performance.

Published
2013

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