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 GaOx (a-GaOx) photo-synapses with an enhanced persistent photoconductivity (PPC) effect. The PPC effect, which induces nonlinearly tunable conductivity, renders the a-GaOx photo-synapses an ideal deep ultraviolet (DUV) photoelectronic reservoir, thus mapping the complex input vector into a dimensionality-reduced output vector. Connecting the reservoirs and a memristor array, we further construct an in-sensor RC system for latent fingerprint identification. The system maintains over 90% recognition accuracy for latent fingerprint within 15% stochastic noise level via the proposed dual-feature strategy. This work provides a subversive prototype system of DUV in-sensor RC for highly efficient recognition of latent fingerprints.

Short-term synaptic plasticity in emerging devices for neuromorphic computing

“…Reproduced from ref. 132 , CC BY license. (F) Handwritten digit recognition using a memristor-based RC system.…”

Nanowire-based synaptic devices for neuromorphic computing

“…NWs synaptic devices can also be used for reservoir computing, which enable to processing temporal and spatial signals [76]. Self-organized Ag NW networks memristive device have been proposed for reservoir computing [77].…”

Bioinspired In‐Sensor Reservoir Computing for Self‐Adaptive Visual Recognition with Two‐Dimensional Dual‐Mode Phototransistors

“…System performance can be augmented through the virtual node technique. [30][31][32][33][34] However, difficulties in modulating the dynamic response of optoelectronic reservoirs result in a relatively fixed nonlinear feature transformation, preventing the system from adapting to tasks under different illumination conditions.…”