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Found 5 papers, 3 papers with code
How Asynchronous Events Encode Video
Instead of recording video by capturing frames, event-based cameras have sensors that emit events when their inputs change, thus encoding information in the timing of events.
A Time Encoding approach to training Spiking Neural Networks
While Spiking Neural Networks (SNNs) have been gaining in popularity, it seems that the algorithms used to train them are not powerful enough to solve the same tasks as those tackled by classical Artificial Neural Networks (ANNs).
Asynchrony Increases Efficiency: Time Encoding of Videos and Low-Rank Signals
Event-based sensing can present significant improvements in power efficiency when compared to traditional sampling, because (1) the output is a stream of events where the important information lies in the timing of the events, and (2) the sensor can easily be controlled to output information only when interesting activity occurs at the input.
Encoding and Decoding Mixed Bandlimited Signals using Spiking Integrate-and-Fire Neurons
We propose a setup to sample a set of bandlimited signals, by mixing them and sampling the result using different IF-TEMs.
Signal Processing
Sampling and Reconstruction of Bandlimited Signals with Multi-Channel Time Encoding
In this paper, we show that, when using time encoding machines, reconstruction from multiple channels has a more intuitive solution, and does not require the knowledge of the shifts between machines.
Signal Processing
