Computer Vision for Embedded Systems

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Course Features

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Duration

5 weeks

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Advanced

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Effort

8 hours per week

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Teaching Type

Instructor Paced

Course Description

This course provides an overview of running computer vision (OpenCV and PyTorch) on embedded systems (such as Raspberry Pi and Jetson). The course emphasizes the resource constraints imposed by embedded systems and examines methods (such as quantization and pruning) to reduce resource requirements. This course will have programming assignments and projects proposed by the students.

Required texts or technologies:

This course does not have a required text. The course will read recently published papers. Students will use Google Colab for programming assignments.

Course Overview

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Live Class

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Human Interaction

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Personlized Teaching

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International Faculty

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Post Course Interactions

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Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Knowledge of Python and Data Science or similar.

What You Will Learn

You will learn how to run computer vision algorithms using OpenCV and PyTorch on embedded systems like Raspberry Pi and Jetson.

You will learn techniques such as quantization and pruning to reduce resource requirements on embedded systems.

You will have the opportunity to work on programming assignments and projects proposed by the students.

Course Instructors

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Yung-Hsiang Lu

Professor of Electrical and Computer Engineering at Purdue University

Yung-Hsiang Lu is a professor of Electrical and Computer Engineering at Purdue University. He is a University Faculty Scholar of Purdue University. He is a fellow of the IEEE (Institute of Electrical...
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Alex Chitsazzadeh

Teaching Assistant at Purdue University

Alex Chitsazzadeh is currently enrolled in a Bachelor of Science in Electrical Engineering program at Purdue University. He is planning on graduating from his undergraduate studies in 2024, and wishe...
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