Issue

Vol. 14 (2022)

Progress of Materials and Devices for Neuromorphic Vision Sensors

https://doi.org/10.1007/s40820-022-00945-y
Sung Woon Cho
Department of Advanced Components and Materials Engineering, Sunchon National University, Sunchŏn, Jeonnam 57922, Republic of Korea
Chanho Jo
Department of Electrical and Electronics Engineering, Chung-Ang University, Seoul 06974, Republic of Korea
Yong‑Hoon Kim
School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
Sung Kyu Park
Department of Electrical and Electronics Engineering, Chung-Ang University, Seoul 06974, Republic of Korea

Corresponding Author: Sung Kyu Park

skpark@cau.ac.kr

Nano-Micro Letters, Vol. 14 (2022), Article Number: 203

Abstract

The latest developments in bio-inspired neuromorphic vision sensors can be summarized in 3 keywords: smaller, faster, and smarter. (1) Smaller: Devices are becoming more compact by integrating previously separated components such as sensors, memory, and processing units. As a prime example, the transition from traditional sensory vision computing to in-sensor vision computing has shown clear benefits, such as simpler circuitry, lower power consumption, and less data redundancy. (2) Swifter: Owing to the nature of physics, smaller and more integrated devices can detect, process, and react to input more quickly. In addition, the methods for sensing and processing optical information using various materials (such as oxide semiconductors) are evolving. (3) Smarter: Owing to these two main research directions, we can expect advanced applications such as adaptive vision sensors, collision sensors, and nociceptive sensors. This review mainly focuses on the recent progress, working mechanisms, image pre-processing techniques, and advanced features of two types of neuromorphic vision sensors based on near-sensor and in-sensor vision computing methodologies.


Highlights:


1 The neuromorphic vision sensors for near-sensor and in-sensor computing of visual information are implemented using optoelectronic synaptic circuits and single-device optoelectronic synapses, respectively.
2 This review focuses on the recent progress, working mechanisms, and image pre-processing techniques about two types of neuromorphic vision sensors based on near-sensor and in-sensor vision computing methodologies.

Keywords

In-sensor computing Near-sensor computing Neuromorphic vision sensor Optoelectronic synaptic circuit Optoelectronic synapse
Cho, Sung Woon, Chanho Jo, Yong‑Hoon Kim, and Sung Kyu Park. 2022. “Progress of Materials and Devices for Neuromorphic Vision Sensors”. Nano-Micro Letters 14 (October):203. https://doi.org/10.1007/s40820-022-00945-y.
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