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Record W3010563898 · doi:10.1038/s41377-020-0261-8

Biologically inspired ultrathin arrayed camera for high-contrast and high-resolution imaging

2020· article· en· W3010563898 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLight Science & Applications · 2020
Typearticle
Languageen
FieldEngineering
TopicImage Processing Techniques and Applications
Canadian institutionsNexen (Canada)
FundersNational Research Foundation of KoreaNational Research Foundation
KeywordsHigh resolutionHigh contrastContrast (vision)Computer scienceBiological imagingSuperresolutionOpticsRemote sensingComputer visionPhysicsGeologyFluorescence

Abstract

fetched live from OpenAlex

Compound eyes found in insects provide intriguing sources of biological inspiration for miniaturised imaging systems. Here, we report an ultrathin arrayed camera inspired by insect eye structures for high-contrast and super-resolution imaging. The ultrathin camera features micro-optical elements (MOEs), i.e., inverted microlenses, multilayered pinhole arrays, and gap spacers on an image sensor. The MOE was fabricated by using repeated photolithography and thermal reflow. The fully packaged camera shows a total track length of 740 μm and a field-of-view (FOV) of 73°. The experimental results demonstrate that the multilayered pinhole of the MOE allows high-contrast imaging by eliminating the optical crosstalk between microlenses. The integral image reconstructed from array images clearly increases the modulation transfer function (MTF) by ~1.57 times compared to that of a single channel image in the ultrathin camera. This ultrathin arrayed camera provides a novel and practical direction for diverse mobile, surveillance or medical applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.863
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.235
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it