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Toward monolithic 3D integration of in-sensor neuromorphic vision systems using metal-oxide semiconductors

Kyungmoon Kwak, Jong Bin An, I. Sak Lee, You Mi Hwang, Hye Jin Son, Hyun Jae Kim

2025Device6 citationsDOIOpen Access PDF

Abstract

Neuromorphic vision systems can realize more compact, and therefore more efficient, computing architectures by integrating sensing, memory, and computing functions on a single platform. Metal-oxide semiconductors play a central role in this transformation due to their electrical characteristics, low-temperature processability, and structural versatility. This review discusses the use of oxide-based optoelectronic synapses, in-memory computing, and logic circuits. Monolithic three-dimensional (M3D) integration is a key enabler of scalable and energy-efficient architectures, and we propose a roadmap for the development of neuromorphic vision systems, including integrated implementations in near- and in-sensor computing. The growing industrial adoption of oxide platforms highlights their technological maturity and practical readiness for next-generation vision systems.

Topics & Concepts

Neuromorphic engineeringMaterials scienceSemiconductorOxideNanotechnologyOptoelectronicsComputer scienceArtificial intelligenceArtificial neural networkMetallurgyAdvanced Memory and Neural ComputingCCD and CMOS Imaging SensorsThin-Film Transistor Technologies