A dual-mode organic memristor for coordinated visual perceptive computing

Abstract

The hierarchically coordinated processing of visual information with the data degradation characteristic embodies the energy consumption minimization and signal transmission efficiency maximization of brain activities. This inspires machine vision to handle the explosively increased data in real-time. In this contribution, we demonstrate the possibility of constructing a coordinated perceptive computing paradigm with dual-mode organic memristors to emulate the visual processing capability of the brain systems. The 32-state modulation of the device photoresponsivity and conductance via photo-induced molecular reconfiguration and electrochemical redox activities enables the execution of computing-in-sensor and computing-in-memory tasks, respectively, which in turn allows the homogeneous hardware integration of a single-layer perceptron and a convolutional neural network for high-efficiency hierarchical visual processing. Compared to the sole optoelectronic CIS mode to recognize visual targets, the dual-mode organic memristor-based coordinated computing scheme demonstrates a 24.5% improvement in the recognition accuracy and 45.8% reduction in the network size.