Transfer Learning can enable you to rapidly deploy AI technologies in your research project by leveraging the existing experience of pre-trained neural networks and tailor it to meet your goals. This webinar will show you how to seamlessly develop a custom neural network classifier based on the GoogleNet pretrained network, via two popular research platforms – the MATLAB® Deep Learning Toolbox™ as well as TensorFlow with Python. The customized neural network will be deployed on both PC as well as embedded targets for use with a variety of Quanser systems such as the QCar, QDrone and QArm.
Murtaza Bohra is the academic lead for the QArm manipulator and has designed the teaching content and research examples available with the arm. He has also designed the application architecture for Quanser’s unmanned vehicles, the QCar and QDrone. With a Masters in Robotics and a background in Aerospace Engineering, both from the University of Toronto, he continues to be involved in academia as a sessional lecturer, teaching a graduate course on serial manipulators and mobile robotics at the University of Toronto.