ysh329/embedded-ai.bi-weekly
WeChat: NeuralTalk，Weekly report and awesome list of embedded-ai.
This project provides a curated weekly report and an extensive list of resources focused on optimizing artificial intelligence models for use on embedded and mobile devices. It compiles information on techniques like model compression, low-bit quantization, and accelerated mobile inference. The target audience includes AI engineers, researchers, and product developers who are challenged with deploying sophisticated AI capabilities onto resource-constrained hardware.
381 stars. No commits in the last 6 months.
Use this if you are an AI developer or researcher looking for the latest techniques and tools to make your neural networks run efficiently on mobile phones, IoT devices, or other embedded systems.
Not ideal if you are looking for an off-the-shelf AI model or a general guide to developing AI applications without a specific focus on embedded systems.
Stars
381
Forks
72
Language
—
License
MIT
Category
Last pushed
Jul 01, 2022
Commits (30d)
0
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