Analysis of Dynamic Visual Prediction Based on In-sensor Computing Network
This paper describes a method of in-sensor computing with multidimensional information to achieve image recognition and prediction.In the work,incorporating the computational theory of reservoir computing(RC)networks,it developed a MoS2-based detector array that functions as a dynamic photoelectronic reservoir,and by leveraging the inherent persistence of photoconductivity(PPC)effect of the detector itself,integrated present and past multi-frame information into a single frame,breaking traditional frame-by-frame computing paradigm.Furthermore,it performed preprocessing on the device to compare the impact of different decay curves on task performance,ultimately accomplishing multi-frame letter transformation classification and word prediction tasks.
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