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» Learning Boosted Asymmetric Classifiers for Object Detection
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CVPR
2007
IEEE
14 years 1 months ago
Matrix-Structural Learning (MSL) of Cascaded Classifier from Enormous Training Set
Aiming at the problem when both positive and negative training set are enormous, this paper proposes a novel Matrix-Structural Learning (MSL) method, as an extension to Viola and ...
Shengye Yan, Shiguang Shan, Xilin Chen, Wen Gao, J...
MICCAI
2007
Springer
14 years 8 months ago
Automatic Fetal Measurements in Ultrasound Using Constrained Probabilistic Boosting Tree
Abstract. Automatic delineation and robust measurement of fetal anatomical structures in 2D ultrasound images is a challenging task due to the complexity of the object appearance, ...
Gustavo Carneiro, Bogdan Georgescu, Sara Good, Dor...
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
11 years 10 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
CVPR
2006
IEEE
14 years 9 months ago
Incremental learning of object detectors using a visual shape alphabet
We address the problem of multiclass object detection. Our aims are to enable models for new categories to benefit from the detectors built previously for other categories, and fo...
Andreas Opelt, Axel Pinz, Andrew Zisserman
ECCV
2008
Springer
14 years 9 months ago
Learning Spatial Context: Using Stuff to Find Things
The sliding window approach of detecting rigid objects (such as cars) is predicated on the belief that the object can be identified from the appearance in a small region around the...
Geremy Heitz, Daphne Koller