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» Is Feature Selection Still Necessary
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HAIS
2010
Springer
13 years 4 months ago
Reducing Dimensionality in Multiple Instance Learning with a Filter Method
In this article, we describe a feature selection algorithm which can automatically find relevant features for multiple instance learning. Multiple instance learning is considered a...
Amelia Zafra, Mykola Pechenizkiy, Sebastián...
IJCNN
2007
IEEE
14 years 1 months ago
Two-stage Multi-class AdaBoost for Facial Expression Recognition
— Although AdaBoost has achieved great success, it still suffers from following problems: (1) the training process could be unmanageable when the number of features is extremely ...
Hongbo Deng, Jianke Zhu, Michael R. Lyu, Irwin Kin...
MTA
2000
165views more  MTA 2000»
13 years 6 months ago
Approximating Content-Based Object-Level Image Retrieval
Object-level image retrieval is an active area of research. Given an image, a human observerdoesnot see randomdots of colors. Rather,he she observesfamiliarobjectsin the image. The...
Wynne Hsu, Tat-Seng Chua, Hung Keng Pung
CVPR
2011
IEEE
12 years 10 months ago
Boosted Local Structured HOG-LBP for Object Localization
Object localization is a challenging problem due to variations in object’s structure and illumination. Although existing part based models have achieved impressive progress in t...
Junge Zhang, Kaiqi Huang, Tieniu Tan
INFOCOM
2000
IEEE
13 years 11 months ago
Trainet: A New Label Switching Scheme
— Trainet, a new scheme to extend MPLS (Multi Protocol Label Switching) is presented. The scheme works much like the subway system in a large metropolitan area. Each (unidirectio...
Yehuda Afek, Anat Bremler-Barr