Time-domain image processing using photonic reservoir computing
EPJ Web of Conferences
Photonic computing has attracted much attention due to its great potential to accelerate artificial neural network operations. However, the processing of a large amount of data, such as image data, basically requires large-scale photonic circuits and is still challenging due to its low scalability of the photonic integration. Here, we propose a scalable image processing approach, which uses a temporal degree of freedom of pho…
Read full excerpt
Photonic computing has attracted much attention due to its great potential to accelerate artificial neural network operations. However, the processing of a large amount of data, such as image data, basically requires large-scale photonic circuits and is still challenging due to its low scalability of the photonic integration. Here, we propose a scalable image processing approach, which uses a temporal degree of freedom of photons. In the proposed approach, the spatial information of a target object is compressively transformed to a time-domain signal using a gigahertz-rate random pattern projection technique. The time-domain signal is optically acquired at a single-input channel and processed with a microcavity-based photonic reservoir computer. We experimentally demonstrate that this photonic approach is capable of image recognition at gigahertz rates.
