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203
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ICASSP
2008
IEEE
16 years 1 months ago
Discriminative feature selection for hidden Markov models using Segmental Boosting
We address the feature selection problem for hidden Markov models (HMMs) in sequence classification. Temporal correlation in sequences often causes difficulty in applying featur...
Pei Yin, Irfan A. Essa, Thad Starner, James M. Reh...
177
Voted
ICPR
2008
IEEE
16 years 1 months ago
Effective scene matching with local feature representatives
Scene matching measures the similarity of scenes in photos and is of central importance in applications where we have to properly organize large amount of digital photos by scene ...
Shugao Ma, Weiqiang Wang, Qingming Huang, Shuqiang...
224
Voted
SMI
2007
IEEE
194views Image Analysis» more  SMI 2007»
16 years 1 months ago
Robust Smooth Feature Extraction from Point Clouds
Defining sharp features in a given 3D model facilitates a better understanding of the surface and aids visualizations, reverse engineering, filtering, simplification, non-photo...
Joel Daniels II, Linh K. Ha, Tilo Ochotta, Cl&aacu...
198
Voted
AMS
2007
Springer
221views Robotics» more  AMS 2007»
16 years 1 months ago
Visual Bearing-Only Simultaneous Localization and Mapping with Improved Feature Matching
Abstract. In this this paper, we present a solution to the simultaneous localization and mapping (SLAM) problem for a robot equipped with a single perspective camera. We track extr...
Hauke Strasdat, Cyrill Stachniss, Maren Bennewitz,...
187
Voted
KBSE
2005
IEEE
16 years 18 days ago
On dynamic feature location
Feature location aims at locating pieces of code that implement a given set of features (requirements). It is a necessary first step in every program comprehension and maintenanc...
Rainer Koschke, Jochen Quante