Evidence map›Paper›PMID 41453880›Full record

ArticleNature communications2025

In-sensor analog optoelectronic processing of concurrent event and memory signals for dynamic vision sensing.

Yelim Kim, Hyeonsu Park, Minjoo Kim, Suhee Jang, Dae Yeop Jeong, Lia Saptini Handriani, Hyuncheol Yun, Namyoung Gwak, Nuri Oh, Sung Ik Yang and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Ion-Exchange-Driven Ternary Organic Neuromorphic Devices with High Efficiency and Stability.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  2. Neuromorphic Devices and Computing for Sensing, Memory, and Control.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  3. 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

13 authors.

Yelim KimDivision of Materials Science and Engineering, Hanyang University, Seoul, Republic of Korea.ORCID http://orcid.org/0009-0009-1254-2863
Hyeonsu ParkDivision of Materials Science and Engineering, Hanyang University, Seoul, Republic of Korea.
Minjoo KimDivision of Materials Science and Engineering, Hanyang University, Seoul, Republic of Korea.
Suhee JangDivision of Materials Science and Engineering, Hanyang University, Seoul, Republic of Korea.
Dae Yeop JeongDivision of Materials Science and Engineering, Hanyang University, Seoul, Republic of Korea.
Lia Saptini HandrianiDivision of Materials Science and Engineering, Hanyang University, Seoul, Republic of Korea.
Hyuncheol YunDivision of Materials Science and Engineering, Hanyang University, Seoul, Republic of Korea.
Namyoung GwakDivision of Materials Science and Engineering, Hanyang University, Seoul, Republic of Korea.
Nuri OhDivision of Materials Science and Engineering, Hanyang University, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0001-9145-8911
Sung Ik YangDepartment of Applied Chemistry, Kyung Hee University, Yongin, Republic of Korea.
Soyeong KwonDepartment of Mechanical and Aerospace Engineering, University of California, Irvine, Irvine, CA, USA.ORCID http://orcid.org/0000-0002-0433-381X
SungWoo NamDepartment of Mechanical and Aerospace Engineering, University of California, Irvine, Irvine, CA, USA.ORCID http://orcid.org/0000-0002-9719-7203
Won Il ParkDivision of Materials Science and Engineering, Hanyang University, Seoul, Republic of Korea. wipark@hanyang.ac.kr.ORCID http://orcid.org/0000-0001-8312-4815

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Efficient dynamic vision requires capturing instantaneous changes and temporal context, yet existing image and event sensors rely on power-hungry digital processing. Here, we introduce an in-sensor dual-response architecture that concurrently generates analog event spikes and persistent memory tails. A prototype sensor integrates phosphor pairs with silicon photodiodes and transimpedance amplifiers to achieve microsecond- and millisecond-scale dual kinetics. Measurements during light-emitting diode replay reconstruct event frames that match software frame differences, while the slow channel behaves as a linear reservoir of motion history. A single memory frame fed to a convolutional neural network enables accurate classification of human actions (93.1%) and vehicle trajectories (98.0%), as well as speed estimation with errors of 2.15 km/h. Integration with a compressive optical neural network front end mapping 4900 inputs to 16 per frame yields 93.3% action classification accuracy. By eliminating analog-to-digital conversion and digital accumulation, this approach enables ultralow-latency, ultralow-power neuromorphic vision.

Identifiers

PMID41453880
PMCPMC12865194

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.