Deep Neural Network on Embedded?

I recently implement couple of algorithms for Deep Learning, which provides fast inference on an embedded devices.

One of them is called ‘LCNN’, you can find the original paper here :

And I implemented it with tensorflow,

This codes compress alexnet which takes roughly 150ms or more on a single core cpu,

to a sparse convolutional layered network which takes 10~50ms on the same environment.


So… based on these new technologies, i am looking for an idea to try.

Like openpose on a robot :

Any Thoughts?


@ildoonet, that’s pretty cool. What embedded platform are you working on? The results are pretty interesting. Well done.

It’s for snapdragon cpus like smartphones.

Also I’m working on arm cpus.

Also, this codes is not optimized for specific cpu architecture, It can be improved further.

That’s really cool!

Do you have trained neural nets to go along with it?

I have alexnet which 20 times faster than the original one. I will add more models. Do you have any particular model you want?