Peery is a highly efficient and infinitely scalable resource and file sharing system which operates by constructing an ad-hoc peer-to-peer network that allows its participants to request and offer machine resources and/or files between one another.
Our goal is to be able to distill the style from an individual's handwriting and generate handwritten text that is indistinguishable by same person's handwriting. Besides having the scientific value of being able to capture style from the content, such a system can be used for bridging the beauty of handwriting and accessibility of digital text. In this regard, we have generated characters in training set then extended it to generating characters seen for the first time. To evaluate our generative network, we've created a game with a purpose (GWAP) application.
Self-driving vehicles are one of the most awaited technology of the last century. After the developments in the field of artificial intelligence, the idea of fully autonomous cars are seemed more possible. In this project, our aim was training a model by using deep learning techniques that can drive a car on different roads. We used Convolutional Neural Network (CNN) due to its pattern recognition and feature extraction capabilities. At the end of the project, our trained model can successfully generalize its knowledge and navigates a car on a completely unknown road.