Computer vision, Deep learning , Artificial Intelligence and Autonomous vehicle enthusiast. Area Worked in • Deep domain expertise in applying machine learning, computer vision and computer graphics to push simulation realism. • Image Segmentation using Deep learning techniques. • Algorithm development for lane tracking using opencv. • Deep learning based Traffic sign classificataion. • Behavioral Training of car for Autonomus driving based on CNN using TensorFlow and Keras. • Lane identification and calculation of the curvature of the road along with the offset calculation of the vehicle from the center of the lane using openCV. • Vehicle detection using machine learning techniques. • Design and Development of mini Unmanned Aerial System for ISR platforms. • Helmet Mount head Tracking and Display system. • Cockpit Displays based on Arinc661, HUD based on Mil-1787B symbology standards • Navigation systems, Digitial Moving Map, Electronic Flight Bag(EFB) based on Arinc 424-18 • PID control loops, Kalman Filter, Extended Kalman Filter, Uncented Kalman Filter and Sensor fusion Algorithm development for MEMS based sensors Specialties: C, C++, Arduino, Python, VC++, Eclipse, Qt, LabWindows CVI \​ LabVIEW, MatLab \​ Simulink, OpenGL, OpenCV, Tensorflow, Keras, ROS MS-Office, X-Plane, JSBSim, FlightGear, SVN & Doors Protocol : Mil-Std-1553B, ARINC 429, RS232, RS422\​485, LXI, GPIB, I2C, CAN , SPI Standards : Arinc661, Arinc424-18, Misra c/c++, DO178B/C. Certified in Aerial Robotics from University of Pennsylvania My github Link: https://github.com/gkbell46