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PPSN
1990
Springer
15 years 6 months ago
Feature Construction for Back-Propagation
T h e ease of learning concepts f r o m examples in empirical machine learning depends on the attributes used for describing the training d a t a . We show t h a t decision-tree b...
Selwyn Piramuthu
148
Voted

Presentation
609views
17 years 1 months ago
Bus transit service planning and operations in a competitive environment
Transit services are currently facing several challenges in the United States and around the world. For many reasons, among which the fluctuations in gas prices and the state of t...
A. M. El-Geneidy, J. Hourdos, J. Horning
179
Voted
CVPR
2009
IEEE
16 years 9 months ago
Active Volume Models for 3D Medical Image Segmentation
In this paper, we propose a novel predictive model for object boundary, which can integrate information from any sources. The model is a dynamic “object” model whose manifes...
Tian Shen (Lehigh University), Hongsheng Li (Lehig...
153
Voted
ICCV
2007
IEEE
16 years 4 months ago
The Best of Both Worlds: Combining 3D Deformable Models with Active Shape Models
Reliable 3D tracking is still a difficult task. Most parametrized 3D deformable models rely on the accurate extraction of image features for updating their parameters, and are pro...
Christian Vogler, Zhiguo Li, Atul Kanaujia, Siome ...
166
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ECCV
2002
Springer
16 years 4 months ago
A Stochastic Algorithm for 3D Scene Segmentation and Reconstruction
In this paper, we present a stochastic algorithm by effective Markov chain Monte Carlo (MCMC) for segmenting and reconstructing 3D scenes. The objective is to segment a range image...
Feng Han, Zhuowen Tu, Song Chun Zhu
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