ArticleScience advances2024
Memory-less scattering imaging with ultrafast convolutional optical neural networks.
Article in Science advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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Who cites it
8 citing papers in PubMed.
- Microwave diffractive neural network chips for sensing and computing.Science advances · 2026Article
- Programmable Optical Megapixel Nano-Kirigami Matrix.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Bio-inspired backpropagation-free training for optical neural networks.Light, science & applications · 2026Article
- Creation of a computational space with model-free metasurface neural network.Nature communications · 2026Article
- Nanosecond-latency all-optical fiber sensing with in-sensor computing.Light, science & applications · 2026Article
- Diffractive Optical Neural Networks: Pathways Toward Intelligent and Scalable Photonic Computing.Nanophotonics (Berlin, Germany) · 2026Review
- Multifunctional movable-type coding metasurface enabling reconfigurable diffractive neural networks.Light, science & applications · 2026Article
- A guidance to intelligent metamaterials and metamaterials intelligence.Nature communications · 2025Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The optical memory effect in complex scattering media including turbid tissue and speckle layers has been a critical foundation for macroscopic and microscopic imaging methods. However, image reconstruction from strong scattering media without the optical memory effect has not been achieved. Here, we demonstrate image reconstruction through scattering layers where no optical memory effect exists, by developing a multistage convolutional optical neural network (ONN) integrated with multiple parallel kernels operating at the speed of light. Training this Fourier optics-based, parallel, one-step convolutional ONN with the strong scattering process for direct feature extraction, we achieve memory-less image reconstruction with a field of view enlarged by a factor up to 271. This device is dynamically reconfigurable for ultrafast multitask image reconstruction with a computational power of 1.57 peta-operations per second (POPS). Our achievement establishes an ultrafast and high energy-efficient optical machine learning platform for graphic processing.
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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.