Cross-Generalization: Learning Novel Classes from a Single Example by Feature Replacement
- 27 July 2005
- proceedings article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 1, 672-679
- https://doi.org/10.1109/cvpr.2005.117
Abstract
No abstract availableThis publication has 11 references indexed in Scilit:
- Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categoriesComputer Vision and Image Understanding, 2007
- Rapid object detection using a boosted cascade of simple featuresPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Sharing features: efficient boosting procedures for multiclass object detectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004
- Learning object detection from a small number of examples: the importance of good featuresPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2004
- Analyzing appearance and contour based methods for object categorizationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Object recognition with informative features and linear classificationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Learning from one example through shared densities on transformsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Visual features of intermediate complexity and their use in classificationNature Neuroscience, 2002
- Combining Class-Specific Fragments for Object ClassificationPublished by British Machine Vision Association and Society for Pattern Recognition ,1999
- Neural network-based face detectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1998