Artificial　visual　systems,　inspired　by　the　human　eye,　hold　significant　potential　in　artificial　intelligence.　Optoelectronic　synapses,　integrating　image　perception,　processing,　and　memory　in　a　single　device,　offer　promising　solutions.　The　human　eye　exhibits　different　recognition　accuracies　for　objects　under　varying　light　conditions.　Therefore,　a　more　biomimetic　visual　system　is　needed　to　better　fit　actual　application　scenarios.　Here,　an　organic　heterojunction-based　optoelectronic　synaptic　transistor　(OHOST)　is　proposed　to　enhance　biomimetic　artificial　visual　systems.　By　utilizing　the　excellent　carrier　capture　ability　of　core-multi-shell　quantum　dots　(QDs)　and　the　high　exciton　dissociation　efficiency　of　heterojunction　interfaces,　the　device　achieves　a　recognition　capability　under　different　light　intensities　closely　resembling　that　of　the　human　eye.　Under　optimal　light　intensity,　the　recognition　accuracy　for　the　modified　national　institute　of　standards　and　technology　(MNIST)　dataset　can　reach　91.52%.　Nevertheless,　under　both　low　and　high　light　intensities,　the　accuracy　drops　to　a　low　level.　This　work　pushes　the　development　of　artificial　visual　systems　toward　higher　levels　of　biomimicry.　An　optoelectronic　synaptic　transistor　based　on　core-multi-shell　quantum　dots　and　Pentacene　achieves　a　recognition　capability　under　different　light　intensities　that　closely　resembles　that　of　the　human　eye.　Under　optimal　light　intensity,　the　recognition　accuracy　for　the　MNIST　dataset　can　reach　91.52%.　Nevertheless,　under　both　low　and　high　light　intensities,　the　accuracy　drops　to　significantly　lower　levels.　image