Главная
Study mode:
on
1
Intro
2
Conventional computer vision (CV) pipeline
3
Compute log from RAW
4
Intuition
5
Energy breakdown of pipelines
6
Overview of CNN experiments
7
Datasets
8
Architecture search: UNAS for microcontrollers
9
Robustness to illumination change
10
Summary
Description:
Explore cutting-edge research on enhancing energy efficiency and robustness in tinyML computer vision applications through a 25-minute talk from the tinyML Research Symposium 2022. Delve into Qianyun LU's presentation on utilizing log-gradient input images to improve CV pipelines for microcontrollers. Learn about conventional CV pipelines, the process of computing log from RAW images, and gain intuition on energy breakdowns. Discover insights from CNN experiments, dataset considerations, and architecture search using UNAS for microcontrollers. Examine the impact on robustness to illumination changes and grasp key takeaways in this comprehensive overview of innovative tinyML techniques.

Improving Energy Efficiency and Robustness of tinyML Computer Vision Using Log-Gradient Input Images

tinyML
Add to list
00:00
-00:45