Retinomorphic Color Perception Based on Opponent Process Enabled by Perovskite Bipolar Photodetectors
Source abstract
Abstract
Abstract The ability to perceive color by the retina can be attributed to both its trichromatic photoreceptors and the antagonistic neural wiring known as the opponent process. While neuromorphic sensors have been shown to demonstrate memory and adaptation capabilities, color perception is still challenging due to the intrinsic lack of spectral selectivity in narrow bandgap semiconductors. Furthermore, research on emulating neural wiring is severely lacking. The combination of halide perovskite materials with a tunable bandgap and a novel bipolar photodetector design emulates the efficiency of the retina in processing color information. The stimuli‐responsive material is also responsible for maintaining partial color constancy—an adaptation feature. Leveraging the unique enhancement of color contrasts, an in‐sensor data compression and edge detection can also be demonstrated. The color perception, chromatic adaptation, and color contrast enhancement make perovskite bipolar photodetectors a unique example where the sensor and neural wiring can be co‐developed in conjunction.
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Research context
OpenAlex topics: Perovskite Materials and Applications · Advanced Memory and Neural Computing · Conducting polymers and applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Materials Science and Engineering Nanyang Technological University 50 Nanyang Avenue Singapore 639798 Singapore
Energy Research Institute @ NTU (ERI@N) Nanyang Technological University 50 Nanyang Drive Singapore 637553 Singapore
School of Computer Science and Engineering Nanyang Technological University 50 Nanyang Avenue Singapore 639798 Singapore
Department of Electrical Engineering City University of Hong Kong 83 Tat Chee Avenue Kowloon Hong Kong SAR 00000 Singapore
Funding
National Research Foundation
References (33)
Show source-provided references
1. Goldstein E. B. · 2002
2. 10.1037/h004140310.1037/h0041403 ↗
3. 10.1097/00006324-200207000-0000510.1097/00006324-200207000-00005 ↗
4. S. H.Schwartz Visual Perception: A Clinical Orientation McGraw Hill Professional 2004.
5. R.Dony S.Wesolkowski inEngineering Solutions for the Next Millennium 1999 IEEE Canadian Conf. Electrical and Computer Engineering (Cat. No. 99TH8411) 687–692 (IEEE).
6. 10.1038/s41565-021-01003-110.1038/s41565-021-01003-1 ↗
7. 10.1002/adma.20220681610.1002/adma.202206816 ↗
8. 10.1088/2053-1583/aa805e10.1088/2053-1583/aa805e ↗
9. 10.1002/adpr.20220017410.1002/adpr.202200174 ↗
10. 10.1002/adma.20220253510.1002/adma.202202535 ↗
11. 10.1021/acsnano.2c0290610.1021/acsnano.2c02906 ↗
12. 10.1038/s41928-022-00713-110.1038/s41928-022-00713-1 ↗
13. 10.1038/s41565-023-01379-210.1038/s41565-023-01379-2 ↗
14. 10.1038/s41565-019-0501-310.1038/s41565-019-0501-3 ↗
15. 10.1021/acsnano.0c0168910.1021/acsnano.0c01689 ↗
16. 10.1016/j.nanoen.2022.10714210.1016/j.nanoen.2022.107142 ↗
17. 10.1002/adma.20190643310.1002/adma.201906433 ↗
18. X.Dong W.Xu Z.Miao L.Ma C.Zhang J.Yang Z.Jin A. B. J.Teoh J.Shen inProc. IEEE/CVF Conf. Computer Vision and Pattern Recognition IEEE New Orleans LA USApp.17431–17440.
19. 10.1109/TIP.2005.85726010.1109/TIP.2005.857260 ↗
20. 10.1038/s41467-022-28374-w10.1038/s41467-022-28374-w ↗
21. 10.1002/adma.20230753410.1002/adma.202307534 ↗
22. 10.1126/science.124316710.1126/science.1243167 ↗
23. 10.1021/acsenergylett.6b0000210.1021/acsenergylett.6b00002 ↗
24. 10.1016/j.joule.2020.03.00510.1016/j.joule.2020.03.005 ↗
25. 10.1016/S0042-6989(99)00033-410.1016/S0042-6989(99)00033-4 ↗
26. K.Yang S.Gao C.Li Y.Li inProc. IEEE Conf. Computer Vision and Pattern Recognition IEEE Portland OR USApp.2810–2817.
27. 10.1038/s41928-024-01124-010.1038/s41928-024-01124-0 ↗
28. 10.1016/S0042-6989(99)00062-010.1016/S0042-6989(99)00062-0 ↗
29. 10.1016/j.visres.2005.06.01610.1016/j.visres.2005.06.016 ↗
30. 10.3389/fnins.2023.120888210.3389/fnins.2023.1208882 ↗
31. 10.1002/adma.20230585710.1002/adma.202305857 ↗
32. 10.1021/acsnano.0c0168910.1021/acsnano.0c01689 ↗
33. 10.1021/acsnano.1c1009810.1021/acsnano.1c10098 ↗