Metric Learning for Large Scale Image Classification: Generalizing to New Classes at Near-Zero Cost
- 1 January 2012
- book chapter
- Published by Springer Nature
Abstract
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This publication has 24 references indexed in Scilit:
- Towards good practice in large-scale learning for image classificationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2012
- Aggregating Local Image Descriptors into Compact CodesIEEE Transactions on Pattern Analysis and Machine Intelligence, 2011
- High-dimensional signature compression for large-scale image classificationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- Large-scale image classification: Fast feature extraction and SVM trainingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- Evaluating knowledge transfer and zero-shot learning in a large-scale settingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- Efficient additive kernels via explicit feature mapsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2010
- Product Quantization for Nearest Neighbor SearchPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2010
- What Does Classifying More Than 10,000 Image Categories Tell Us?Published by Springer Nature ,2010
- TagProp: Discriminative metric learning in nearest neighbor models for image auto-annotationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2009
- ImageNet: A large-scale hierarchical image databasePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2009