Agenda of the Webinar

Stage 1: 10 mins -Introduction to Embedded Systems and Computer Vision.
Stage 2: 10 mins -Introduction to software, tools, and languages. S
tage 3: 25 mins - Basics of Computer Vision.
Stage 4: 25 mins - Introduction to Embedded Systems and selection of controllers for standalone applications.
Stage 5: 25 mins - Initializing computer vision projects over raspberry pi for object detection.
Stage 6: 15 mins - Introduction to CNN, one-stage and two-stage object detection.
Stage 7: 10 mins Briefing on career opportunities and upskilling in the field of Embedded Systems and Computer Vision.

Tools Used:

Python - Language, Raspbian OS, and Computer Vision libraries.
Jupyter Notebook - IDE (Integrated Development Environment)

Learning Outcome

At the end of the workshop, the learners will be able to:
-Understand the basics of computer vision and its importance in engineering applications.
-Interpret the integration for standalone applications using Embedded devices.
-Understand various API's of the OpenCV library.
-Understand the importance of neural networks in computer vision and running lite versions on embedded devices.

About the Instructor

Dadi Ravikanth is a Senior Technical Support Engineer in Autonomous Vehicles at Skill-Lync. He has 7+ years of experience in the field of Robotics and Automation. He has worked as Assistant Professor for 6 years at the Manipal Academy of Higher Education, educating students on ROS, Localization and Mapping, Embedded Systems for Machine Learning, Predictive Algorithms, and Open Computer Vision. He specializes in Haptics and perception psychology and has published SCI & Scopus journals in the field of perception psychology for applied sciences.