Ruijter, R.J.A. de (2017) The Effect of pooling the Hidden Activation in a Patch-Based Image Classification System using Multi-Layer Perceptrons. Bachelor's Thesis, Artificial Intelligence.
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Abstract
In this thesis a patch-based image classification system using a multi-layer perceptron (MLP) system is proposed. The patch-based MLP is trained on a set of randomly selected patches from the training images. This method is also used in a design where multiple patch-based MLPs are trained on specific regions of the images, this is called the scoped patch-based MLP system. Both the patch-based MLP and the scoped patch-based MLP system are used as a feature extractor for a classifier as well. The performance of these approaches are tested on the MNIST and CIFAR-10 datasets, where 99.43% and 71.63% classification accuracy are obtained, respectively.
| Item Type: | Thesis (Bachelor's Thesis) |
|---|---|
| Degree programme: | Artificial Intelligence |
| Thesis type: | Bachelor's Thesis |
| Language: | English |
| Date Deposited: | 15 Feb 2018 08:26 |
| Last Modified: | 15 Feb 2018 08:26 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/14828 |
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