ArticleNational science review2025
Rational design of a vision fusion system with visible and near-infrared spectral integration for improved environmental perception.
Article in National science review, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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.
Who cites it
2 citing papers in PubMed.
- In-sensor multispectral perception for near- and mid-infrared discrimination.Nature communications · 2026Article
- Polarization reversal and ion-electron co-modulation in in-plane anisotropic AgVPNature communications · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the rapid advancements in autonomous driving, pure vision-based solutions have garnered significant attention. However, existing vision sensors are limited by their specific spectral operating ranges and the complexity of processing hybrid optical/electrical signals. In this study, we present a fully circuit-emulated vision system that employs a vision fusion solution for autonomous driving, integrating image sensing, fusion, edge extraction, and decision-making functionalities. This system utilizes vision sensors featuring an Al
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Registered trials
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.