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Record W2021688092 · doi:10.1364/ao.47.004121

Active optical system for variable view imaging of micro objects with emphasis on kinematic analysis

2008· article· en· W2021688092 on OpenAlexaff
Xiaodong Tao, Hyungsuck Cho, Farrokh Janabi‐Sharifi

Bibliographic record

VenueApplied Optics · 2008
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Vision and Imaging
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsWorkspaceKinematicsComputer scienceTracingComputer visionRay tracing (physics)RoboticsArtificial intelligenceForward kinematicsPrismOpticsMachine visionInverse kinematicsRobotPhysics

Abstract

fetched live from OpenAlex

Insufficient vision information, such as occlusion, low resolvability, and a small field of view, represent important issues in microassembly and micromanipulation. We propose an active optical system to solve problems related to insufficient vision information through the integration of robotics and optics technologies. The proposed system integrates a double-prism system and a scanning mirror system to supply a compact flexible view. The kinematics of the imaging system is analyzed based on a simplified model initially to investigate the workspace and identify the kinematic performance. A more rigorous analysis of kinematics of the system is then made based on the ray tracing method. The simulation results based on the preliminary design are provided for investigating the workspace and demonstrating the capability of the system in imaging with variable views.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.247
Teacher spread0.236 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations34
Published2008
Admission routes1
Has abstractyes

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