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ICPR
2008
IEEE
16 years 5 months ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
ICRA
2010
IEEE
177views Robotics» more  ICRA 2010»
15 years 3 months ago
Fusion of laser and vision for multiple targets tracking via on-line learning
— Multi-target tracking becomes significantly more challenging when the targets are in close proximity or frequently interact with each other. This paper presents a promising tr...
Xuan Song, Huijing Zhao, Jinshi Cui, Xiaowei Shao,...
151
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MSOM
2007
118views more  MSOM 2007»
15 years 4 months ago
What Can Be Learned from Classical Inventory Models? A Cross-Industry Exploratory Investigation
: Classical inventory models offer a variety of insights into the optimal way to manage inventories of individual products. However, top managers and industry analysts are often co...
Sergey Rumyantsev, Serguei Netessine
GEOS
2009
Springer
15 years 9 months ago
Bottom-Up Gazetteers: Learning from the Implicit Semantics of Geotags
As directories of named places, gazetteers link the names to geographic footprints and place types. Most existing gazetteers are managed strictly top-down: entries can only be adde...
Carsten Keßler, Patrick Maué, Jan Tor...
NIPS
1998
15 years 6 months ago
Learning to Estimate Scenes from Images
We seek the scene interpretation that best explains image data. For example, we may want to infer the projected velocities (scene) which best explain two consecutive image frames ...
William T. Freeman, Egon C. Pasztor