My research so far has been focused on computer vision and machine learning, specifically visual recognition and deep learning.
During my Master of Science degree at department of computer engineering, Sharif University of Technology, I was a member of IPL under supervision of Prof. Shohreh Kasaei. I also had the privilege to work closely with Dr. Erik Rodner for my thesis. I finished my Bachelors of Science at school of computer engineering, Iran University of Science and Technology where I worked with Dr. Soryani and Dr. Rahmani for my undergrad thesis.
CV available upon request.
Persian Handwritten Digit Recognition by Random Forest and Convolutional Neural Networks
Yasin Zamani, Yaser Souri, Hossein Rashidi, Shohreh Kasaei
Aug 2017 - present
University of Bonn
Under supervision of Prof. J. Gall
Sep 2013 - Mar 2015
Relative Attributes are a very natural way of thinking in terms of attributes and communicating with machines. The idea was introduced in the award winning ICCV 2011 paper by D. Parikh and K. Grauman. In this project we want to improve their system by using a Deep Neural Network instead of a RankSVM to do the ranking. This way we can also use Convolutional Layers to learn the features end-to-end.
Code: Lasagne, Theano, Python
A fast way to detect bird parts (e.g. head) using pre-pixel deep features and random forests is introduced. Then using the detected part locations we can do fine-grained recognition on CUB-200-2011. Our mean accuracy is 72.02% which is comparable with state-of-the-art (73.89%) while being at least 2 orders of magnitude faster when detecting parts. Our method only uses a single forward pass of the network to detect parts.
Code: Python, Caffe, Scikit-learn
An original implementation of Criminisi's image impainting algorithm for a course project.
Code: OpenCV and C++