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ICPR
2010
IEEE
13 years 7 months ago
Fast Training of Object Detection Using Stochastic Gradient Descent
Training datasets for object detection problems are typically very large and Support Vector Machine (SVM) implementations are computationally complex. As opposed to these complex ...
Rob Wijnhoven, Peter H. N. De With
EUROGP
2005
Springer
13 years 10 months ago
Understanding Evolved Genetic Programs for a Real World Object Detection Problem
We describe an approach to understanding evolved programs for a real world object detection problem, that of finding orthodontic landmarks in cranio-facial X-Rays. The approach in...
Victor Ciesielski, Andrew Innes, Sabu John, John M...
ICIP
2008
IEEE
14 years 6 months ago
LASIC: A model invariant framework for correspondence
In this paper we address two closely related problems. The first is the object detection problem, i.e., the automatic decision of whether a given image represents a known object o...
Bernardo Rodrigues Pires, João Xavier, Jos&...
ECCV
2006
Springer
14 years 6 months ago
Object Detection by Contour Segment Networks
We propose a method for object detection in cluttered real images, given a single hand-drawn example as model. The image edges are partitioned into contour segments and organized i...
Vittorio Ferrari, Tinne Tuytelaars, Luc J. Van Goo...
ECCV
2004
Springer
14 years 6 months ago
Reliable Fiducial Detection in Natural Scenes
Reliable detection of fiducial targets in real-world images is addressed in this paper. We show that even the best existing schemes are fragile when exposed to other than laborator...
David Claus, Andrew W. Fitzgibbon