Semantic Font Attribution Using Deep Learning


Semantic Font Attribution Using Deep Learning – An automatic font recognition (BSR) system is presented in this paper. A novel architecture is designed to recognize the characters in a large font of high quality. The system includes two features: character similarity maps (CSMs) for the recognition, based on a novel convolutional neural network approach. Each CSM encodes the character at the same level as the corresponding font with the information needed to train the CSM. The system is presented in this report.

There have been a number of research projects that have investigated and evaluated the performance of machine learning methods on two data sets (one of which is a time series of two people using a mobile phone) as a means for realising a user’s behaviour towards the data sets. In this paper, we investigate the impact of deep learning on machine learning algorithms on our future research. We will propose to study the deep learning techniques using Deep Neural Networks for object recognition tasks where objects are occluded by background noises.

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Semantic Font Attribution Using Deep Learning

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  • End-to-end Deep Image Retrieval using Pervasive Conditioning

    Learning to detect and eliminate spurious events from unstructured analysis of time seriesThere have been a number of research projects that have investigated and evaluated the performance of machine learning methods on two data sets (one of which is a time series of two people using a mobile phone) as a means for realising a user’s behaviour towards the data sets. In this paper, we investigate the impact of deep learning on machine learning algorithms on our future research. We will propose to study the deep learning techniques using Deep Neural Networks for object recognition tasks where objects are occluded by background noises.


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