ArticleNature communications2024
Hardware-accelerated integrated optoelectronic platform towards real-time high-resolution hyperspectral video understanding.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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
3 citing papers in PubMed.
- MOCLIP: a foundation model for large-scale nanophotonic inverse design.Nature communications · 2026Article
- Metaoptics merging computational optics and optical computing toward intelligent visual perception.Science advances · 2026Review
- From spectrum to yield: advances in crop photosynthesis with hyperspectral imaging.Photosynthetica · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent advancements in artificial intelligence have significantly expanded capabilities in processing language and images. However, the challenge of comprehensively understanding video content still needs to be solved. The main problem is the requirement to process real-time multidimensional video information at data rates exceeding 1 Tb/s, a demand that current hardware technologies cannot meet. This work introduces a hardware-accelerated integrated optoelectronic platform specifically designed for the real-time analysis of multidimensional video. By leveraging optical information processing within artificial intelligence hardware and combining it with advanced machine vision networks, the platform achieves data processing speeds of 1.2 Tb/s. This capability supports the analysis of hundreds of frequency bands with megapixel spatial resolution at video frame rates, significantly outperforming existing technologies in speed by three to four orders of magnitude. The platform demonstrates effectiveness for AI-driven tasks, such as video semantic segmentation and object understanding, across indoor and aerial scenarios. By overcoming the current data processing speed limitations, the platform shows promise in real-time AI video understanding, with potential implications for enhancing human-machine interactions and advancing cognitive processing technologies.
Identifiers
What OpenQuestion holds
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.