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NPL
2006
172views more  NPL 2006»
13 years 8 months ago
Adapting RBF Neural Networks to Multi-Instance Learning
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Min-Ling Zhang, Zhi-Hua Zhou
TIP
2002
131views more  TIP 2002»
13 years 8 months ago
Optimal edge-based shape detection
Abstract--We propose an approach to accurately detecting twodimensional (2-D) shapes. The cross section of the shape boundary is modeled as a step function. We first derive a one-d...
Hankyu Moon, Rama Chellappa, Azriel Rosenfeld
ICIP
2010
IEEE
13 years 6 months ago
Building Emerging Pattern (EP) Random forest for recognition
The Random forest classifier comes to be the working horse for visual recognition community. It predicts the class label of an input data by aggregating the votes of multiple tree...
Liang Wang, Yizhou Wang, Debin Zhao
ICCV
2011
IEEE
12 years 8 months ago
Learning Universal Multi-view Age Estimator by Video Contexts
Most existing techniques for analyzing face images assume that the faces are at near-frontal poses. Generalizing to non-frontal faces is often difficult, due to a dearth of groun...
Zheng Song, Bingbing Ni, Dong Guo, Terence Sim, Sh...
CVPR
1999
IEEE
14 years 10 months ago
Background Estimation and Removal Based on Range and Color
Background estimation and removal based on the joint use of range and color data produces superior results than can be achieved with either data source alone. This is increasingly...
Gaile G. Gordon, Trevor Darrell, Michael Harville,...