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Related Experiment Video

Updated: Jun 8, 2026

Measurement of Tension Release During Laser Induced Axon Lesion to Evaluate Axonal Adhesion to the Substrate at Piconewton and Millisecond Resolution
09:31

Measurement of Tension Release During Laser Induced Axon Lesion to Evaluate Axonal Adhesion to the Substrate at Piconewton and Millisecond Resolution

Published on: May 27, 2013

Neural-network laser radar.

K Lizuka, S Fujii

    Applied Optics
    |October 2, 2010
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a laser radar with sub-micrometer resolution. Neural network processing significantly improved resolution for applications in materials science and optical device analysis.

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    Area of Science:

    • Optoelectronics
    • Materials Science
    • Signal Processing

    Background:

    • High-resolution measurement is critical for microscale defect detection and material characterization.
    • Existing radar processing methods, like Fourier-transform-based processing, have limitations in achieving superior resolution.

    Purpose of the Study:

    • To report a novel laser radar system with resolution exceeding 1 µm.
    • To demonstrate the application of this laser radar in various scientific and industrial contexts.
    • To evaluate the efficacy of neural-network-based signal processing for enhanced radar resolution.

    Main Methods:

    • Development of a laser radar system capable of sub-micrometer resolution.
    • Application of the laser radar for void sizing in silicon wafers.

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    Last Updated: Jun 8, 2026

    Measurement of Tension Release During Laser Induced Axon Lesion to Evaluate Axonal Adhesion to the Substrate at Piconewton and Millisecond Resolution
    09:31

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    Published on: May 27, 2013

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  • Profiling optical fiber cross-sections.
  • Birefringence study of lithium-niobate crystals.
  • Fault detection in optical integrated circuits.
  • Utilizing neural-network theory for laser radar signal processing.

    • Main Results:

    • The laser radar achieved a resolution greater than 1 µm.
    • Demonstrated successful application in diverse material and device analyses.
    • Neural-network-based processing yielded significantly superior resolution compared to Fourier-transform methods.

    Conclusions:

    • The developed laser radar system offers high resolution for microscale metrology.
    • Neural-network signal processing is a powerful technique for enhancing laser radar performance.
    • This technology has broad applicability in quality control and research for optical and semiconductor industries.