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» Learning Mid-Level Features For Recognition
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AIR
1998
160views more  AIR 1998»
13 years 7 months ago
Automatic Plankton Image Recognition
Plankton form the base of the food chain in the ocean and are fundamental to marine ecosystem dynamics. The rapid mapping of plankton abundance together with taxonomic and size com...
Xiaoou Tang, W. Kenneth Stewart, He Huang, Scott M...
ICCV
2009
IEEE
13 years 5 months ago
Selection and context for action recognition
Recognizing human action in non-instrumented video is a challenging task not only because of the variability produced by general scene factors like illumination, background, occlu...
Dong Han, Liefeng Bo, Cristian Sminchisescu
ICMLC
2005
Springer
14 years 1 months ago
Adaptive Online Multi-stroke Sketch Recognition Based on Hidden Markov Model
This paper presents a novel approach for adaptive online multi-stroke sketch recognition based on Hidden Markov Model (HMM). The method views the drawing sketch as the result of a ...
Zhengxing Sun, Wei Jiang, Jianyong Sun
ICIP
2009
IEEE
13 years 5 months ago
Selecting representative and distinctive descriptors for efficient landmark recognition
To have a robust and informative image content representation for image categorization, we often need to extract as many as possible visual features at various locations, scales a...
Sheng Gao, Joo-Hwee Lim
CVPR
2011
IEEE
13 years 3 months ago
What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms
In real-world applications, “what you saw” during training is often not “what you get” during deployment: the distribution and even the type and dimensionality of features...
Brian Kulis, Kate Saenko, Trevor Darrell