A 201.4 GOPS real-time multi-object recognitionprocessor is presented with a three-stage pipelined architecture.Visual perception based multi-object recognition algorithm isapplied to give multiple attentions to multiple objects in the inputimage. For human-like multi-object perception, a neural perceptionengine is proposed with biologically inspired neural networksand fuzzy logic circ
KIMetal.:A201.4GOPS496mWREAL-TIMEMULTI-OBJECTRECOGNITIONPROCESSORWITHBIO-INSPIREDNEURALPERCEPTIONENGINE
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Fig.3.Overallblockdiagramofproposed
processor.
Fig.4.Three-stagepipelinedarchitecture.
proportionaltotheamountofworkload,theexecutiontimeoftheoveralldescriptorgenerationstageiskeptinconstant.Theoverallexecutiontimeisadjustedbymodifyingthresholdvaluesofclassi cationprocess.Byloweringthresholdvalues,theexecutiontimeisdecreasedbecausemoreSPUsareas-signedforthesameamountofworkload.Ontheotherhand,theexecutiontimeincreaseswhenthresholdvaluesbecomehigh,whilethenumberofoperatingSPUsisreduced.
Tocontroltheexecutiontimeofobjectdecisionstage,theSTMperformsapplieddatabasesizecontrol(ADSC),showninFig.5(b).BasedonthevectormatchingalgorithmoftheDP[12],theoverallexecutiontimeoftheobjectdecisionstageis