Thesiss

Multimodal biometric systems have been widely applied in many real-world applications due to its ability to deal with a number of significant limitations of unimodal biometric systems, including sensitivity to noise, population coverage, intra-class variability, non-universality…

Early efforts to predict the spread of disease have been traced back to the 14 th century. Most notable in historical disease prediction is the Black Death which engulfed Europe from 1347 to 1351, killing an estimated 200 million people. Attempts to predict the spread of disease…

In this research, we propose to use deep learning to predict crimes in small neighborhoods (regions) of a city, by using historical crime data collected from the past. The motivation of crime predictions is that if we can predict the number crimes that will occur in a certain we…

An important analysis in fluorescence spectroscopy is molecular dynamics, in particular, quantification of diffusion coefficient. In this research, we apply a convolutional neural network (CNN) to determine the diffusion coefficient of freely diffusing molecules. We construct th…

Deep learning is a new area of machine learning in artificial intelligence that consists of networks to learn representations from data in a supervised, semi-supervised and unsupervised manner. Deep learning has a relatively long history, but it does not gain great attention unt…