Evidence map›Paper›PMID 38877323›Full record

ReviewNature nanotechnology2024

Multidimensional vision sensors for information processing.

Zhaoqing Wang, Tianqing Wan, Sijie Ma, Yang Chai

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature nanotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

37 citing papers in PubMed.

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  7. Bioinspired Photodetectors: From Nature to Advanced Applications.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Zhaoqing Wang *Department of Applied Physics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.
Tianqing Wan *Department of Applied Physics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.
Sijie MaDepartment of Applied Physics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.
Yang ChaiDepartment of Applied Physics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China. ychai@polyu.edu.hk.ORCID http://orcid.org/0000-0002-8943-0861

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The visual scene in the physical world integrates multidimensional information (spatial, temporal, polarization, spectrum and so on) and typically shows unstructured characteristics. Conventional image sensors cannot process this multidimensional vision data, creating a need for vision sensors that can efficiently extract features from substantial multidimensional vision data. Vision sensors are able to transform the unstructured visual scene into featured information without relying on sophisticated algorithms and complex hardware. The response characteristics of sensors can be abstracted into operators with specific functionalities, allowing for the efficient processing of perceptual information. In this Review, we delve into the hardware implementation of multidimensional vision sensors, exploring their working mechanisms and design principles. We exemplify multidimensional vision sensors built on emerging devices and silicon-based system integration. We further provide benchmarking metrics for multidimensional vision sensors and conclude with the principle of device-system co-design and co-optimization.

Identifiers

What OpenQuestion holds

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Registered trials

None linked

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.