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Official PyTorch implementation of paper "A Hybrid Compact Neural Architecture for Visual Place Recognition" by M. Chancán (RA-L & ICRA 2020) https://doi.org/10.1109/LRA.2020.2967324

Home Page: https://mchancan.github.io/projects/FlyNet

License: MIT License

Python 100.00%
bio-inspired brain-inspired neural-networks place-recognition recurrent-neural-networks visual-localization

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flynet's Issues

About the CANN code

Hello,

I really liked the architecture built by you and was trying to simulate the experiments. Can you please clarify what exactly the code for CANN is achieving? Is it for training or inference?

Thanks

CANN Implementation

Hi,

Great work, but I was wondering if there is any code available regarding the CANN network, as in the paper the implementation is of Flynet + CANN.
Any help would be appreciated !!

About flynet + CANN

Hi! Excellent work you did.

I have some quesitons about flynet +CANN.
fn

As shown above,the output of MLP is a probability score of each input image,and each neuron of CANN linearly connect to MLP.
So how CANN process the output data of MLP?
And what is the input unit V ?
And the output of CANN is max activity of n neurons,isn't it?

Looking forward to your kindly reply~

Minor change to the main.py

Great piece of work! As the function fna is part of the main.py, line 12 from models import fna can be removed. As otherwise main.py do not run.

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