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» Learning at Low False Positive Rates
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CVPR
2007
IEEE
14 years 9 months ago
Parameter Sensitive Detectors
Object detection can be challenging when the object class exhibits large variations. One commonly-used strategy is to first partition the space of possible object variations and t...
Quan Yuan, Ashwin Thangali, Vitaly Ablavsky, Stan ...
CVPR
2007
IEEE
13 years 11 months ago
Improving Part based Object Detection by Unsupervised, Online Boosting
Detection of objects of a given class is important for many applications. However it is difficult to learn a general detector with high detection rate as well as low false alarm r...
Bo Wu, Ram Nevatia
CEAS
2007
Springer
14 years 1 months ago
Asymmetric Gradient Boosting with Application to Spam Filtering
In this paper, we propose a new asymmetric boosting method, Boosting with Different Costs. Traditional boosting methods assume the same cost for misclassified instances from di...
Jingrui He, Bo Thiesson
DAGM
2007
Springer
14 years 1 months ago
A Fast and Reliable Coin Recognition System
This paper presents a reliable coin recognition system that is based on a registration approach. To optimally align two coins we search for a rotation in order to reach a maximal n...
Marco Reisert, Olaf Ronneberger, Hans Burkhardt
PST
2008
13 years 9 months ago
Investigating Two Different Approaches for Encrypted Traffic Classification
The basic objective of this work is to compare the utility of an expert driven system and a data driven system for classifying encrypted network traffic, specifically SSH traffic ...
Riyad Alshammari, A. Nur Zincir-Heywood