Weak Hypotheses and Boosting for Generic Object Detection and Recognition

Andreas Opelt; Michael Fussenegger; Axel Pinz; Peter Auer

doi:10.1007/978-3-540-24671-8_6

Keywords

Boosting (machine learning)Discriminative modelArtificial intelligenceComputer scienceCognitive neuroscience of visual object recognitionPattern recognition (psychology)ComputationObject (grammar)Machine learningAlgorithm

Affiliated Institutions

Graz University of Technology AT

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Publication Info

Year: 2004
Type: book-chapter
Pages: 71-84
Citations: 265
Access: Closed

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APA Style

                            
                                    Andreas Opelt, 
                                
                                    Michael Fussenegger, 
                                
                                    Axel Pinz
                                
                                et al.
                            
                            (2004). 
                            Weak Hypotheses and Boosting for Generic Object Detection and Recognition. 
                            Lecture notes in computer science
                            
                            , 71-84.
                            https://doi.org/10.1007/978-3-540-24671-8_6

Identifiers

DOI: 10.1007/978-3-540-24671-8_6