专题：Surface Roughness and Optical Measurements

This cluster of papers focuses on the characterization and measurement of surface roughness in optical components, utilizing techniques such as fractal analysis, machine vision, scattering theory, and thin film analysis. The research covers topics such as surface roughness measurement, power spectral density analysis, micromorphology characterization, and the application of image processing for evaluating surface roughness.
最新文献
Metasurface-enabled single-shot and complete Mueller matrix imaging

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A visual measurement method of grinding surface roughness based on aliasing region index and neural network

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Semi-supervised surface defect segmentation of aluminum strips based on self-attention consistency and cross-view pseudo supervision

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The end-to-end chip surface defect segmentation method based on the diffusion model and attention mechanism

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Correlation between electrical and structural changes in amorphous ITO films

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Steel surface defect detection based on PSO-Gabor and an improved faster RCNN

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Surface defect detection algorithm for copper strip based on SCAP enhancement

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On-machine measurement and compensation for thin-walled surfaces using LLT sensors

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Laser power modulation for improving laser soldering defects via LSTM and CNN models

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Cellular Regression Machine: A Collaborative Modeling Approach for Batch BRDF Reconstruction and Infrared Emissivity Prediction of Non-Lambertian Surfaces

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近5年高被引文献
State of the Art in Defect Detection Based on Machine Vision

article Full Text OpenAlex 610 FWCI60.70454629

Surface Defect Detection Methods for Industrial Products: A Review

review Full Text OpenAlex 319 FWCI30.73073042

Image-Based Surface Defect Detection Using Deep Learning: A Review

review Full Text OpenAlex 272 FWCI27.70307225

Development of a YOLO-V3-based model for detecting defects on steel strip surface

article Full Text OpenAlex 262 FWCI32.54732532

Improved faster R-CNN for fabric defect detection based on Gabor filter with Genetic Algorithm optimization

article Full Text OpenAlex 247 FWCI24.37264826

Automated surface defect detection framework using machine vision and convolutional neural networks

article Full Text OpenAlex 219 FWCI34.72546127

The Handbook of Surface Imaging and Visualization

book Full Text OpenAlex 213 FWCI2.11937717

Modelling and prediction of surface roughness in wire arc additive manufacturing using machine learning

article Full Text OpenAlex 212 FWCI18.52020865

Recent advances in surface defect inspection of industrial products using deep learning techniques

article Full Text OpenAlex 211 FWCI22.10190463

Defect Detection Methods for Industrial Products Using Deep Learning Techniques: A Review

review Full Text OpenAlex 200 FWCI57.1027454