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» Learning at Low False Positive Rates
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CVPR
2007
IEEE
16 years 1 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
15 years 3 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
15 years 6 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
15 years 6 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
15 years 1 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