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» Learning Models for Object Recognition
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CVPR
2007
IEEE
16 years 5 months ago
Modelling Objects using Distribution and Topology of Multiscale Region Pairs
We propose a method for simultaneous detection, localization and segmentation of objects of a known category. We show that this is possible by using segments as features. To this ...
Himanshu Arora, Narendra Ahuja
ECCV
2006
Springer
16 years 5 months ago
A Boundary-Fragment-Model for Object Detection
The objective of this work is the detection of object classes, such as airplanes or horses. Instead of using a model based on salient image fragments, we show that object class det...
Andreas Opelt, Axel Pinz, Andrew Zisserman
ECAI
2010
Springer
15 years 18 days ago
Adaptive Markov Logic Networks: Learning Statistical Relational Models with Dynamic Parameters
Abstract. Statistical relational models, such as Markov logic networks, seek to compactly describe properties of relational domains by representing general principles about objects...
Dominik Jain, Andreas Barthels, Michael Beetz
ICASSP
2011
IEEE
14 years 7 months ago
Efficient block-division model for robust multiple object tracking
Tracking multiple objects under occlusion is one of the most challenging issues in computer vision. Occlusion results in mistaken match when finding the most similar candidate. A...
Wenhan Luo, Xiaoqin Zhang, Yang Liu, Xi Li, Weimin...
ISMIS
2005
Springer
15 years 8 months ago
Learning the Daily Model of Network Traffic
Abstract. Anomaly detection is based on profiles that represent normal behaviour of users, hosts or networks and detects attacks as significant deviations from these profiles. In t...
Costantina Caruso, Donato Malerba, Davide Papagni