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» A comparative study of two object recognition methods
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PVLDB
2010
86views more  PVLDB 2010»
15 years 2 months ago
Swarm: Mining Relaxed Temporal Moving Object Clusters
Recent improvements in positioning technology make massive moving object data widely available. One important analysis is to find the moving objects that travel together. Existin...
Zhenhui Li, Bolin Ding, Jiawei Han, Roland Kays
152
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ASUNAM
2010
IEEE
15 years 3 months ago
A Multiobjective and Evolutionary Clustering Method for Dynamic Networks
—The discovery of evolving communities in dynamic networks is an important research topic that poses challenging tasks. Previous evolutionary based clustering methods try to maxi...
Francesco Folino, Clara Pizzuti
CVPR
2005
IEEE
16 years 6 months ago
Object Detection Using 2D Spatial Ordering Constraints
Object detection is challenging partly due to the limited discriminative power of local feature descriptors. We amend this limitation by incorporating spatial constraints among ne...
Yan Li, Yanghai Tsin, Yakup Genc, Takeo Kanade
ECCV
2008
Springer
16 years 6 months ago
A Fast Algorithm for Creating a Compact and Discriminative Visual Codebook
In patch-based object recognition, using a compact visual codebook can boost computational efficiency and reduce memory cost. Nevertheless, compared with a large-sized codebook, it...
Lei Wang, Luping Zhou, Chunhua Shen
ICPR
2006
IEEE
16 years 5 months ago
Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning
It is possible to broadly characterize two approaches to probabilistic modeling in terms of generative and discriminative methods. Provided with sufficient training data the discr...
B. Michael Kelm, Chris Pal, Andrew McCallum