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» Connectivity graphs as models of local interactions
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CVPR
2004
IEEE
13 years 11 months ago
Modeling Complex Motion by Tracking and Editing Hidden Markov Graphs
In this paper, we propose a generative model for representing complex motion, such as wavy river, dancing fire and dangling cloth. Our generative method consists of four component...
Yizhou Wang, Song Chun Zhu
BMCBI
2007
142views more  BMCBI 2007»
13 years 7 months ago
LinkHub: a Semantic Web system that facilitates cross-database queries and information retrieval in proteomics
nd: A key abstraction in representing proteomics knowledge is the notion of unique identifiers for individual entities (e.g. proteins) and the massive graph of relationships among...
Andrew K. Smith, Kei-Hoi Cheung, Kevin Y. Yip, Mar...
WPES
2006
ACM
14 years 1 months ago
Private social network analysis: how to assemble pieces of a graph privately
Connections in distributed systems, such as social networks, online communities or peer-to-peer networks, form complex graphs. These graphs are of interest to scientists in field...
Keith B. Frikken, Philippe Golle
IJON
2007
81views more  IJON 2007»
13 years 7 months ago
Statistical analysis of spatially embedded networks: From grid to random node positions
Many conceptual studies of local cortical networks assume completely random wiring. For spatially extended networks, however, such random graph models are inadequate. The geometry...
Nicole Voges, Ad Aertsen, Stefan Rotter
ECCV
2010
Springer
14 years 1 months ago
Graph Cut based Inference with Co-occurrence Statistics
Abstract. Markov and Conditional random fields (CRFs) used in computer vision typically model only local interactions between variables, as this is computationally tractable. In t...