Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

TinyML Talks - Low-Power Computer Vision

tinyML via YouTube

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore low-power computer vision technologies in this 31-minute tinyML Talks webcast featuring Yung-Hsiang Lu from Purdue University. Discover energy-efficient solutions for battery-powered systems, including parameter quantization, compressed convolutional filters, network architecture search, and knowledge distillation. Learn about hierarchical neural networks for reducing energy consumption on embedded systems and get introduced to the IEEE International Low-Power Computer Vision Challenge. Gain insights into recent research, challenges, and open questions in the field of low-power computer vision.

Syllabus

Introduction
YungHsiang Lu
LowPower Computer Vision
Outline
Quantization
ImageNet
Network Architecture Search
Distillation
Questions
Data Sets
Benchmarks
Recent research
Challenges
Paper
Open Questions
CVD Challenge
LPC Vida
Summary
Question
Survey Paper
tinyML Talk Sponsors
Edge Impulse
Sincents
Next talk
Thanks

Taught by

tinyML

Reviews

Start your review of TinyML Talks - Low-Power Computer Vision

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.