Image dataset to train a deep learning model to decode Leetspeak obfuscated characters

The dataset contains an image database (18,981 images) that could be used to train a deep learning model to accurately detect characters. We have successfully used it to create a model that identifies characters encoded using LeetSpeak. The original dataset can be found in the Mondragon Unibertsitatea Repository -- https://gitlab.danz.eus/datasharing/ski4spam The training dataset consists of: - Alphabetic letters (a-z) written using different fonts and styles (regular, cursive, bold, cursive+bold) - Handwritten letters: English handwriting from the Chars74k dataset [2] which is available at http://www.ee.surrey.ac.uk/CVSSP/demos/chars74k/.

Related Organizations

Iscte - Instituto Universitário de Lisboa
Portugal
Mondragon University
Spain
Universidade de Vigo
Spain

Keywords

Deep Learning, Convolutional Neural Networks, Leetspeak, Text Deobfuscation, Spam filtering

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