Comments (2)
i think the difference is that asynet propagate event-by-event.
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That is correct. The difference between SSC and asynet is the possibility to propagate single events through the network. Due to the rule book formulation and the network state propagation through time, asynet reduces the number of FLOPS required to process single events or small batches of events. In comparison, SCC compute the activations of active sites even if the input did not change. This is not the case for asynet due to the network state propagation through time.
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Related Issues (20)
- where does the accuracy come from? HOT 11
- how can we make asynet trainable? HOT 3
- an error when training with gpu HOT 3
- Some question about code on reading N-Cars dataset HOT 6
- Training times
- Help with using asynet for object detection HOT 5
- Bug HOT 1
- Error while running Object Detection HOT 4
- Error compiling async_sparse_py HOT 3
- Questions about Prophesee dataset
- Help of running time HOT 1
- How to compute FLOPs HOT 1
- Codes relevant to Prophesse dataset experiments?
- Unable to make dataset for N-Cars HOT 1
- Failed to run "pip install async_sparse_py/" HOT 1
- I want to use DVS128 dataset, what should I do?
- How to use the model to detect?
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- Check for a broken link: git clone https://gitlab.com/libeigen/eigen.git --branch 3.4.0-rc1
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