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» Multiple kernel learning and feature space denoising
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ACCV
2007
Springer
15 years 9 months ago
Combined Object Detection and Segmentation by Using Space-Time Patches
This paper presents a method for classifying the direction of movement and for segmenting objects simultaneously using features of space-time patches. Our approach uses vector quan...
Yasuhiro Murai, Hironobu Fujiyoshi, Takeo Kanade
104
Voted
NAACL
2007
15 years 4 months ago
Kernel Regression Based Machine Translation
We present a novel machine translation framework based on kernel regression techniques. In our model, the translation task is viewed as a string-to-string mapping, for which a reg...
Zhuoran Wang, John Shawe-Taylor, Sándor Sze...
KDD
2007
ACM
276views Data Mining» more  KDD 2007»
16 years 3 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
141
Voted
CVPR
2011
IEEE
14 years 11 months ago
Sharing Features Between Objects and Their Attributes
Visual attributes expose human-defined semantics to object recognition models, but existing work largely restricts their influence to mid-level cues during classifier training....
Sung Ju Hwang, Fei Sha, Kristen Grauman
ECCV
2010
Springer
15 years 8 months ago
Object, Scene and Actions: Combining Multiple Features for Human Action Recognition
Abstract. In many cases, human actions can be identified not only by the singular observation of the human body in motion, but also properties of the surrounding scene and the rel...