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Computer Vision for Embedded Systems

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.

What you'll learn

  • i. Use computer vision to analyze images.
  • ii. List the constraints of embedded systems.
  • iii. Explore design space of computer vision.
  • iv. Evaluate different methods for accuracy/time tradeoffs.
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Length 5 weeks
Effort 5 weeks, 7–8 hours per week
Starts On Demand (Start anytime)
Cost $750
From Purdue University via edX
Instructors Yung-Hsiang Lu, Alex Chitsazzadeh
Download Videos On all desktop and mobile devices
Language English
Tags Engineering

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Rating Not enough ratings
Length 5 weeks
Effort 5 weeks, 7–8 hours per week
Starts On Demand (Start anytime)
Cost $750
From Purdue University via edX
Instructors Yung-Hsiang Lu, Alex Chitsazzadeh
Download Videos On all desktop and mobile devices
Language English
Tags Engineering

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