Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categories
Top Cited Papers
- 1 April 2007
- journal article
- Published by Elsevier in Computer Vision and Image Understanding
- Vol. 106 (1), 59-70
- https://doi.org/10.1016/j.cviu.2005.09.012
Abstract
No abstract availableThis publication has 8 references indexed in Scilit:
- A Bayesian approach to unsupervised one-shot learning of object categoriesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Saliency, Scale and Image DescriptionInternational Journal of Computer Vision, 2001
- A Computational Model for Visual SelectionNeural Computation, 1999
- Object recognition from local scale-invariant featuresPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1999
- An Introduction to Variational Methods for Graphical ModelsMachine Learning, 1999
- A probabilistic approach to object recognition using local photometry and global geometryPublished by Springer Nature ,1998
- Local grayvalue invariants for image retrievalIEEE Transactions on Pattern Analysis and Machine Intelligence, 1997
- Recognition-by-components: A theory of human image understanding.Psychological Review, 1987