In-sensor reservoir computing system for latent fingerprint recognition with deep ultraviolet photo-synapses and memristor array

Abstract Detection and recognition of latent fingerprints play crucial roles in identification and security. However, the separation of sensor, memory, and processor in conventional ex-situ fingerprint recognition system seriously deteriorates the latency of decision-making and inevitably increases the overall computing power. In this work, a photoelectronic reservoir computing (RC) system, consisting of DUV photo-synapses and nonvolatile memristor array, is developed to detect and recognize the latent fingerprint with in-sensor and parallel in-memory computing. Through the Ga-rich design, we achieve amorphous GaO x (a-GaO x ) photo-synapses with an enhanced persistent photoconductivity (PPC) effect. The PPC…

• NN
  National Natural Science Foundation of China

  Awards: 51961145110, U20A20207, 62004186, 62004184, and 51961145110, 62104044, 61825404, 61925110
• CA
  Chinese Academy of Sciences

  Award: QYZDB-SSW-JSC048
• CP
  China Postdoctoral Science Foundation

  Awards: BX20200320, 2020M671895
• UO
  University of Science and Technology of China
• SI
  Suzhou Institute of Nanotechnology, Chinese Academy of Sciences