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» Learning Boosted Asymmetric Classifiers for Object Detection
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PAKDD
2004
ACM
137views Data Mining» more  PAKDD 2004»
14 years 27 days ago
Fast and Light Boosting for Adaptive Mining of Data Streams
Supporting continuous mining queries on data streams requires algorithms that (i) are fast, (ii) make light demands on memory resources, and (iii) are easily to adapt to concept dr...
Fang Chu, Carlo Zaniolo
ECCV
2010
Springer
13 years 8 months ago
Object of Interest Detection by Saliency Learning
In this paper, we present a method for object of interest detection. This method is statistical in nature and hinges in a model which combines salient features using a mixture of l...
ECCV
2002
Springer
14 years 9 months ago
A Tale of Two Classifiers: SNoW vs. SVM in Visual Recognition
Numerous statistical learning methods have been developed for visual recognition tasks. Few attempts, however, have been made to address theoretical issues, and in particular, stud...
Ming-Hsuan Yang, Dan Roth, Narendra Ahuja
ECCV
2008
Springer
14 years 9 months ago
Simultaneous Detection and Registration for Ileo-Cecal Valve Detection in 3D CT Colonography
Object detection and recognition has achieved a significant progress in recent years. However robust 3D object detection and segmentation in noisy 3D data volumes remains a challen...
Le Lu, Adrian Barbu, Matthias Wolf, Jianming Liang...
NIPS
2004
13 years 9 months ago
The power of feature clustering: An application to object detection
We give a fast rejection scheme that is based on image segments and demonstrate it on the canonical example of face detection. However, instead of focusing on the detection step w...
Shai Avidan, Moshe Butman