Imaginea de profil a utilizatorului hafizas101
@hafizas101
Membru din 22 septembrie 2019
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hafizas101

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Hi.. I am an enthusiast in Machine learning and Robotics with skills in Python, Machine learning, Deep learning, Computer Vision, MATLAB, ROS, gazebo and C language. I have done several deep learning related projects whose details are available on my Github profile [login to view URL] My Bachelor's education is in Electronics and electrical engineering and currently I am doing MSc Robotics. I have been working on the following projects: ✅ Vehicle pose estimation in crowded and crossroad scenarios ✅ROS-based Integration of smart space and mobile robot as Internet of Robotic Things ✅ Deep learning based human activity recognition ✅ Real time human pose estimation using OpenPose ✅ Indoor scenes recognition using CNN ✅ Face detection and recognition using Haar cascade and CNN ✅ Stock price prediction using Autoregressive and LSTM models I would like to work for all kinds of Deep Learning/Machine Learning/Artificial Intelligence/Data Science projects.
$20 USD/hr
27 recenzii
5.0
  • 97%Proiecte finalizate
  • 100%Conform bugetului
  • 100%La timp
  • 21%Rata de angajare repetată

Portfolio Items

Păreri Recente

Experiență

Junior researcher

Aug 2018 - Jul 2017 (1 month)

I have learnt several software related technical skills at Innopolis University. I am working my thesis "Vehicle pose estimation in crowded and crossroad scenarios". I developed my skills in Python, MATLAB, Machine learning, Deep learning, Computer Vision and OpenCV, ROS, Gazebo.

Educație

BSc Electrical Engineering

2014 - 2018 (4 years)

MSc Robotics

2018 - 2019 (1 year)

Calificări

ROS for Beginners: Basics motion and OpenCV by Anis Kouba (2019)

Udemy.com

ROS for Beginners II: Localization, Navigation and SLAM by Anis koubaa. (2019)

Udemy.com

Machine Learning by Andrew NG (2018)

Stanford University

Publicări

ROS-based Integration of smart space and mobile robot as Internet of Robotic Things

In this project, we are able to detect and classify objects by leveraging the services provided by the smart space infrastructure using a low-end lego ev3 mobile robot with no computer vision abilities. Communication is established between robot and a desktop PC using ROS.

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