Wanningen, A. (2016) A Primal Support Vector Machine for Handwritten Character Recognition using a Bag of Visual Words. Bachelor's Thesis, Artificial Intelligence.
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Abstract
Using a bag of visual words for unsupervised feature learning, a system of handwritten character recognition is developed using a support vector machine (SVM) for which the update rules are derived directly from the primary objective function. The system is tested on the MNIST dataset and outperforms a traditional SVM implementation in this particular set-up, not only in terms of accuracy but most notably in terms of computation time. Whether this approach should be labelled as part of the SVM family of algorithms remains a point of discussion.
| Item Type: | Thesis (Bachelor's Thesis) |
|---|---|
| Degree programme: | Artificial Intelligence |
| Thesis type: | Bachelor's Thesis |
| Language: | English |
| Date Deposited: | 15 Feb 2018 08:25 |
| Last Modified: | 15 Feb 2018 08:25 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/14697 |
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