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» Detect2Rank: Combining Object Detectors Using Learning to Ra...
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WWW
2011
ACM
12 years 11 months ago
Learning to rank with multiple objective functions
We investigate the problem of learning to rank for document retrieval from the perspective of learning with multiple objective functions. We present solutions to two open problems...
Krysta Marie Svore, Maksims Volkovs, Christopher J...
VIP
2003
13 years 6 months ago
Using Dual Cascading Learning Frameworks for Image Indexing
To bridge the semantic gap in content-based image retrieval, detecting meaningful visual entities (e.g. faces, sky, foliage, buildings etc) in image content and classifying images...
Joo-Hwee Lim, Jesse S. Jin
CVPR
2001
IEEE
14 years 6 months ago
Rapid Object Detection using a Boosted Cascade of Simple Features
This paper describes a machine learning approach for visual object detection which is capable of processing images extremely rapidly and achieving high detection rates. This wor...
Paul A. Viola, Michael J. Jones
AVSS
2006
IEEE
13 years 8 months ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks
CVPR
2009
IEEE
2216views Computer Vision» more  CVPR 2009»
15 years 2 days ago
Object Detection using a Max-Margin Hough Transform
We present a discriminative Hough transform based ob- ject detector where each local part casts a weighted vote for the possible locations of the object center. We show that the ...
Subhransu Maji (University of California, Berkeley...