Principles of artificial intelligence
Principles of artificial intelligence
The nature of statistical learning theory
The nature of statistical learning theory
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Matching and Indexing of Graph Models in Content-Based Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Proceedings of the First International Workshop on Multiple Classifier Systems
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Automatic Linguistic Indexing of Pictures by a Statistical Modeling Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image recognition for digital libraries
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Feature selection for graph-based image classifiers
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
Support vector machines for histogram-based image classification
IEEE Transactions on Neural Networks
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In this paper, we propose an approach to image content recognition that exploits the benefits of different image representations to associate meaning with images. We choose classifiers based on global appearance, scene structure and region type occurrence, and define confidence measures on their output. The resulting posterior probabilities of the classifiers are combined in a Bayesian framework. We show that this method leads to a robust and efficient system that contributes to reducing the semantic gap between low level image features and higher level image descriptions.