Name: Muhammad Talha Ejaz
Type: User
Company: Georgia Institute of Technology
Bio: Summer Intern @ Georgia Institute of Technology |
Research Assistant (Robotics) @ Columbus State University
Topics: Machine Learning, Computer Vision, UGV
Location: Atlanta
Blog: https://talhaejazh.github.io/
Muhammad Talha Ejaz's Projects
citizen science + data science project
This repo contains famous data structure problems and solutions
The goal of this project is for Clearpath Jackal to autonomously navigate and map an unknown area using SLAM in Melodic and frontier exploration algorithm based on laser data from a Velodyne VLP-16 LIDAR .
Implementing Computer Vision Algorithm using Python
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
In this repository, we developed an IMU-based indoor localization system using the GY-521 module, which has both a gyroscope and an accelerometer. The first phase of the project involved capturing raw data, and the second phase involved plotting and implementing three filters: Kalman Filter, Extended Kalman Filter, and Unscented Kalman Filter
This repositories show the difference between instance and semantic segmentation using PixelLib
Self-supervised Deep LiDAR Odometry for Robotic Applications
Scrapping Linked In Pages for a particular company's employees
Scalable machine ๐ค learning for time series forecasting.
Learn OpenCV : C++ and Python Examples
Config files for my GitHub profile.
A small prototype of the self-driving car using a Convolutional Neural Network. This is my course project to implement an end-to-end method for training convolutional neural networks for the autonomous navigation of a mobile robot. The proposed navigation system shows object detection. The vehicle it is used can directly output the linear velocity of the robot from an input image in a single step. The trained model gives wheel velocities for navigation as outputs in real-time making it possible to be implanted on mobile robots such as robotic vacuum cleaners. The experimental results show an average linear velocity with a maximum turning angle is 30 degrees. The proposed model built in python 3.0 and experimental tests based on small scale car Quanser latest self-driving car (QCar) state-of-the-art product equipped with Jetson TX2 has been conducted to verify the effectiveness of the proposed network.
protfolio