REAL-TIME OBJECT RECOGNITION WITH NEURO-FUZZY CONTROLLED WORKLOAD-AWARE TASK PIPELINING

Abstract

A PROPOSED OBJECT RECOGNITION PROCESSOR LIGHTENS ITS WORKLOAD BY ESTIMATING GLOBAL REGION-OF-INTEREST FEATURES. A NEURO-FUZZY CONTROLLER PERFORMS INTELLIGENT ROI ESTIMATION BY MIMICKING THE HUMAN VISUAL SYSTEM, THEN MANAGES THE PROCESSOR'S OVERALL PIPELINE STAGES USING WORKLOAD-AWARE TASK SCHEDULING AND APPLIED DATABASE SIZE CONTROL. THE NFC PERFORMS WORKLOAD-AWARE DYNAMIC POWER MANAGEMENT TO REDUCE THE PROPOSED PROCESSOR'S POWER CONSUMPTION.