ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2020
Learned Integrated Sensing Pipeline: Reconfigurable Metasurface Transceivers as Trainable Physical Layer in an Artificial Neural Network.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 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
34 citing papers in PubMed.
- Novel 1-bit hybrid reconfigurable intelligent surface.Scientific reports · 2026Article
- XOR-Logic Phase Coding Programmable Metasurface for Low Power-Consumption Systems.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Cyber metasurface system for electromagnetic field closed-loop sensing and manipulation.Communications engineering · 2026Article
- Flexible intelligent microwave metasurface with shape-guided adaptive programming.Nature communications · 2025Article
- Electromagnetic metamaterial agent.Light, science & applications · 2025Article
- Semantic-Electromagnetic Inversion With Pretrained Multimodal Generative Model.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Phasor-based analysis of a neuromorphic architecture for microwave sensing.Scientific reports · 2024Article
- Multichannel highly secure wireless communication system with information camouflage capability.Science advances · 2024Article
- Semantic regularization of electromagnetic inverse problems.Nature communications · 2024Article
- Microwave Speech Recognizer Empowered by a Programmable Metasurface.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Experimentally realized physical-model-based frugal wave control in metasurface-programmable complex media.Nature communications · 2024Article
- Unleashing the potential: AI empowered advanced metasurface research.Nanophotonics (Berlin, Germany) · 2024Review
- Intelligent indoor metasurface robotics.National science review · 2023Article
- Fast Near-Field Frequency-Diverse Computational Imaging Based on End-to-End Deep-Learning Network.Sensors (Basel, Switzerland) · 2022Article
- Highly Thermally Conductive Adhesion Elastomer Enhanced by Vertically Aligned Folded Graphene.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Article
- Artificial Intelligence in Meta-optics.Chemical reviews · 2022Review
- Origami Microwave Imaging Array: Metasurface Tiles on a Shape-Morphing Surface for Reconfigurable Computational Imaging.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Article
- Meta-optic accelerators for object classifiers.Science advances · 2022Article
- Dielectric metalens for miniaturized imaging systems: progress and challenges.Light, science & applications · 2022Review
- Metasurface-enabled on-chip multiplexed diffractive neural networks in the visible.Light, science & applications · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid proliferation of intelligent systems (e.g., fully autonomous vehicles) in today's society relies on sensors with low latency and computational effort. Yet current sensing systems ignore most available a priori knowledge, notably in the design of the hardware level, such that they fail to extract as much task-relevant information per measurement as possible. Here, a "learned integrated sensing pipeline" (LISP), including in an end-to-end fashion both physical and processing layers, is shown to enable joint learning of optimal measurement strategies and a matching processing algorithm, making use of a priori knowledge on task, scene, and measurement constraints. Numerical results demonstrate accuracy improvements around 15% for object recognition tasks with limited numbers of measurements, using dynamic metasurface apertures capable of transceiving programmable microwave patterns. Moreover, it is concluded that the optimal learned microwave patterns are nonintuitive, underlining the importance of the LISP paradigm in current sensorization trends.
Indexed as
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.