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TRECVID
2008
13 years 9 months ago
Learning TRECVID'08 High-Level Features from YouTube
Run No. Run ID Run Description infMAP (%) training on TV08 data 1 IUPR-TV-M SIFT visual words with maximum entropy 6.1 2 IUPR-TV-MF SIFT with maximum entropy, fused with color+tex...
Adrian Ulges, Christian Schulze, Markus Koch, Thom...
IROS
2009
IEEE
168views Robotics» more  IROS 2009»
14 years 2 months ago
A stream-based hierarchical anchoring framework
— Autonomous systems situated in the real world often need to recognize, track, and reason about various types of physical objects. In order to allow reasoning at a symbolic leve...
Fredrik Heintz, Jonas Kvarnström, Patrick Doh...
PAMI
2006
187views more  PAMI 2006»
13 years 7 months ago
An Experimental Study on Pedestrian Classification
Detecting people in images is key for several important application domains in computer vision. This paper presents an in-depth experimental study on pedestrian classification; mul...
Stefan Munder, Dariu M. Gavrila
CVPR
2010
IEEE
14 years 3 months ago
Online Multiple Instance Learning with No Regret
Multiple instance (MI) learning is a recent learning paradigm that is more flexible than standard supervised learning algorithms in the handling of label ambiguity. It has been u...
Li Mu, James Kwok, Lu Bao-liang
ICIP
2010
IEEE
13 years 5 months ago
Robust segmentation of lung tissue in chest CT scanning
This paper deals with segmentation of the lung tissues from low dose CT (LDCT) scans of the chest. Goal is correct segmentation as well as maintaining the details of the lung regi...
Amal A. Farag, James Graham, Aly Farag