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» Measuring and Predicting Object Importance
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MOBIHOC
2010
ACM
14 years 9 months ago
Fine-grained mobility characterization: steady and transient state behaviors
Recent popularization of personal hand-held mobile devices makes it important to characterize the mobility pattern of mobile device users, so as to accurately predict user mobilit...
Wei Gao, Guohong Cao
VLSM
2005
Springer
15 years 4 months ago
Uncertainty-Driven Non-parametric Knowledge-Based Segmentation: The Corpus Callosum Case
Abstract. In this paper we propose a novel variational technique for the knowledge based segmentation of two dimensional objects. One of the elements of our approach is the use of ...
Maxime Taron, Nikos Paragios, Marie-Pierre Jolly
WSCG
2004
232views more  WSCG 2004»
15 years 19 days ago
Robust Tracking of Athletes Using Multiple Features of Multiple Views
This paper presents a robust and reconfigurable object tracker that integrates multiple visual features from multiple views. The tandem modular architecture stepwise refines the e...
Toshihiko Misu, Seiichi Gohshi, Yoshinori Izumi, Y...
GIS
2002
ACM
14 years 11 months ago
Aggregation and comparison of trajectories
Dealing with moving objects necessitates having available complete geographical traces for determining exact or possible locations that objects have had, have or will have. This i...
Nirvana Meratnia, Rolf A. de By
ICTAI
2006
IEEE
15 years 5 months ago
Sustained Emerging Spatio-Temporal Co-occurrence Pattern Mining: A Summary of Results
Sustained emerging spatio-temporal co-occurrence patterns (SECOPs) represent subsets of object-types that are increasingly located together in space and time. Discovering SECOPs i...
Mete Celik, Shashi Shekhar, James P. Rogers, James...