Timing Decomposition and Strategy Trade-Offs in Contrast Detection Autofocus Under Platform Capability Constraints.

Ximing Zhang, Rui Hai, Yulin Wang, Weiping Liu

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ximing ZhangCollege of Instrumentation and Electrical Engineering, Jilin University, 938 West Democracy Avenue, Changchun 130061, China.

Rui HaiCollege of Instrumentation and Electrical Engineering, Jilin University, 938 West Democracy Avenue, Changchun 130061, China.

Yulin WangCollege of Instrumentation and Electrical Engineering, Jilin University, 938 West Democracy Avenue, Changchun 130061, China.

Weiping LiuCollege of Instrumentation and Electrical Engineering, Jilin University, 938 West Democracy Avenue, Changchun 130061, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Contrast detection autofocus (CDAF) performance in industrial machine vision is shaped by platform capability as well as by the focus measure and search strategy. CDAF is analyzed through a platform capability framework and a unified frame-level transaction chain across three platforms: a capability upper-bound platform (P1), a bridging platform (P2), and an industrial black-box platform (P3). In experiments covering six scene categories, four initial conditions, five fixed-rule strategies, and 30 repetitions per condition, the dominant observable tail on P3 is localized after control submission, in the command-to-actuation segment. On P2, controlled one-factor perturbations using a physically calibrated sample position mismatch intensity (σ

Indexed as

contrast detection autofocuscontrolled perturbation injectionframe-level transaction chainindustrial machine visionlatency decompositionperformance envelopeplatform capability constraintsstrategy trade-offs

Identifiers

PMID42356743

DOI10.3390/s26123770

PMCPMC13306768

What OpenQuestion holds

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LicenceCC BY

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Registered trials

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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.