Groefsema, M. (2016) Deep Architectures using the Bag of Words Model for Object and Handwritten Character Recognition. Bachelor's Thesis, Artificial Intelligence.
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Abstract
This thesis describes an image classification system, using feature extraction, the Bag of Visual Words model (BoW), a Deep Bag of Visual Words model (DBoW) and a Support Vector Machine (SVM) classifier. The performance of the system using the BoW model is compared to the performance using the DBoW model. The performances are assessed using 10-fold cross-validations on the MNIST and CIFAR-10 datasets. First different configurations are explored of both the BoW model and the DBoW model. Finally, both architectures are compared based on their best performances. Results show a lower performance by using the DBoW architecture compared to the performance using the BoW model.
| Item Type: | Thesis (Bachelor's Thesis) |
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| Degree programme: | Artificial Intelligence |
| Thesis type: | Bachelor's Thesis |
| Language: | English |
| Date Deposited: | 15 Feb 2018 08:13 |
| Last Modified: | 15 Feb 2018 08:13 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/14115 |
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