Abstract
Traditional machine vision is suffering from redundant sensing data, bulky structures, and high energy consumption. Biological-inspired neuromorphic systems are promising for compact and energy-efficient machine vision. Multifunctional optoelectronics enabling multispectrum sensitivity for broadband image sensing, feature extraction, and neuromorphic computing are vital for machine visions. Here, an optoelectronic synapse is designed that enables image sensing, convolutional processing, and computing. Multiple synaptic plasticity triggered by photons can implement photonic computing and information transmission. Convolutional processing is realized by ultralow energy kernel generators fully controlled by photons. Meanwhile, the device shows the ability of conductance modulations under electronic stimulations that implement neuromorphic computing. For the first time, this two-terminal broadband optoelectronic synapse enables front-end retinomorphic image sensing, convolutional processing, and back-end neuromorphic computing. The integrated photonic information encryption, convolutional image preprocessing, and neuromorphic computing capabilities are promising for compact monolithic neuromorphic machine vision systems.
| Original language | English |
|---|---|
| Article number | 2303879 |
| Journal | Advanced Functional Materials |
| Volume | 33 |
| Issue number | 49 |
| DOIs | |
| State | Published - 1 Dec 2023 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- convolutional neural networks
- multispectrum sensitivity
- neuromorphic computing
- optoelectronic synapses
- resistive switching
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