Neuromorphic vision system shows 92.17% accuracy in image processing, suggesting advancement in robotics.
Driven by the rapid progress of artificial intelligence and robotics, neuromorphic vision systems are gaining significant attention for enabling efficient visual information processing in complex and dynamic environments. In particular, optoelectronic devices that emulate the functionality of the biological retina are essential for achieving efficient neuromorphic visual processing. Here, we report an optoelectronic synaptic memtransistor (OSMT)‐based neuromorphic vision system for image processing applications. By integrating photoresponsive indium–gallium–zinc–oxide (IGZO) as the channel material with a hafnium oxide (HfO 2 ) contact‐engineered architecture, the OSMT exhibits optically and electrically tunable resistive states, enabling stable and controllable synaptic weight modulation for artificial neural network (ANN) implementation. Benefiting from reliable optoelectronic synaptic characteristics, ANN simulations achieve a handwritten digit recognition accuracy of 92.17%. Furthermore, a 6 × 6 OSMT array demonstrates neuromorphic image processing capabilities, including contrast enhancement. These results highlight the potential of OSMTs as key building blocks for intelligent machine vision systems, offering new opportunities for advanced robotic platforms and human–machine interfaces.
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Kang et al. (2026) studied this question.
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