Evidence map›Paper›PMID 36242681›Full record

ReviewNano-micro letters2022

Progress of Materials and Devices for Neuromorphic Vision Sensors.

Sung Woon Cho, Chanho Jo, Yong-Hoon Kim, Sung Kyu Park

Abstract readReview
In one paragraph

Review in Nano-micro letters, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed.

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  18. Optoelectronic Devices for In-Sensor Computing.Advanced materials (Deerfield Beach, Fla.) · 2025
    Article
  19. Efficient Photothermoelectric Conversion of CSS@BP/BiAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

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 KimSchool of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon, 16419, Republic of Korea. yhkim76@skku.edu.
Sung Kyu ParkDepartment of Electrical and Electronics Engineering, Chung-Ang University, Seoul, 06974, Republic of Korea. skpark@cau.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

In-sensor computingNear-sensor computingNeuromorphic vision sensorOptoelectronic synapseOptoelectronic synaptic circuit

Identifiers

PMID36242681
PMCPMC9569410

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.