Bionic visual processing hardware serves as the core technology for mimicking the efficient information processing of biological vision systems and forms the foundation for perceiving and recognizing both static and dynamic scenes. However, most current bionic visual hardware remains at the level of individual devices and simple arrays. Full hardware implementation of bionic vision chips, as well as comprehensive demonstrations in practical application scenarios, is still scarce. This work proposes a complete optoelectronic insect-inspired visual sensor. We realize a Si QDs/ReS2 heterogeneous integrated neuromorphic chip fabricated using a 180-nm CMOS process technology and demonstrate its capabilities on both static and dynamic visual tasks. Based on the wavelength-dependent synaptic properties of ReS2, this neuromorphic photoreceptor chip exhibits high-fidelity discrimination between purple and red features. Through light pulse sequence modulation, it achieves temporal encoding of dynamic visual information and can precisely identify leaf movement trajectories in eight directions. We further achieved 3D perception capabilities, attaining 99.4% accuracy in classification tasks. This work establishes a novel 1D/2D/3D heterogeneously integrated material platform and a CMOS-compatible integration strategy for a low-power, multifunctional brain-inspired neuromorphic sensor chip, advancing the application of optoelectronic devices in artificial intelligence and machine vision.
Chai et al. (Tue,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: