Decision Combination in Multiple Classifier Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improved Boosting Algorithms Using Confidence-rated Predictions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
Experimental evaluation of expert fusion strategies
Pattern Recognition Letters - Special issue on pattern recognition in practice VI
Signal Processing - Special section on content-based image and video retrieval
A new use of the ridgelets transform for describing linear singularities in images
Pattern Recognition Letters
A general framework for the evaluation of symbol recognition methods
International Journal on Document Analysis and Recognition
A new shape descriptor defined on the Radon transform
Computer Vision and Image Understanding
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In this paper we propose an original solution to combine the scales of multi-resolution shape descriptors. More precisely, a classifier fusion scheme is applied to a set of shape descriptors obtained from the ridgelets transform. The Ridgelets coefficients are grouped into different descriptors according to their resolution. Then a classifier is trained for each descriptor and a final classification is obtained using the classifier fusion scheme. We have applied this approach to symbol recognition using the GREC 2003 database. In this perspective, we increase the recognition rates of previous works on ridgelets-based descriptors.