# Industrial Vision Systems and Defect Detection

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/industrial-vision-systems-and-defect-detection/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the application of machine vision, texture analysis, and deep learning techniques for the automated detection and classification of fabric defects in industrial settings, particularly in semiconductor manufacturing. The research covers various methods such as Gabor filters, wafer map defect classification, and virtual metrology to enhance the accuracy and efficiency of fabric defect detection systems. |
| Domain | Physical Sciences |
| Field | Engineering |
| OpenAlex ID | t12111 |
| Works | 202 |

## Topic papers all

Showing 15 of 202.

- [2012 IEEE Conference on Computer Vision and Pattern Recognition](https://scholariq.org/papers/2012-ieee-conference-on-computer-vision-and-pattern-recognition/)
- [Deep learning for smart manufacturing: Methods and applications](https://scholariq.org/papers/deep-learning-for-smart-manufacturing-methods-and-applications/)
- [Machine learning in manufacturing: advantages, challenges, and applications](https://scholariq.org/papers/machine-learning-in-manufacturing-advantages-challenges-and-applications/)
- [Recent advances and trends in predictive manufacturing systems in big data environment](https://scholariq.org/papers/recent-advances-and-trends-in-predictive-manufacturing-systems-in-big-data/)
- [Industrial Artificial Intelligence for industry 4.0-based manufacturing systems](https://scholariq.org/papers/industrial-artificial-intelligence-for-industry-4-0-based-manufacturing-systems/)
- [Industrial Artificial Intelligence in Industry 4.0 - Systematic Review, Challenges and Outlook](https://scholariq.org/papers/industrial-artificial-intelligence-in-industry-4-0-systematic-review-challenges/)
- [Smart Manufacturing and Intelligent Manufacturing: A Comparative Review](https://scholariq.org/papers/smart-manufacturing-and-intelligent-manufacturing-a-comparative-review/)
- [The smart factory as a key construct of industry 4.0: A systematic literature review](https://scholariq.org/papers/the-smart-factory-as-a-key-construct-of-industry-4-0-a-systematic-literature/)
- [A Convolutional Neural Network for Fault Classification and Diagnosis in Semiconductor Manufacturing Processes](https://scholariq.org/papers/a-convolutional-neural-network-for-fault-classification-and-diagnosis-in/)
- [Research on data augmentation for image classification based on convolution neural networks](https://scholariq.org/papers/research-on-data-augmentation-for-image-classification-based-on-convolution/)
- [Convolutional Neural Network for Wafer Surface Defect Classification and the Detection of Unknown Defect Class](https://scholariq.org/papers/convolutional-neural-network-for-wafer-surface-defect-classification-and-the/)
- [Improving failure analysis efficiency by combining FTA and FMEA in a recursive manner](https://scholariq.org/papers/improving-failure-analysis-efficiency-by-combining-fta-and-fmea-in-a-recursive/)
- [Machine Learning approach for Predictive Maintenance in Industry 4.0](https://scholariq.org/papers/machine-learning-approach-for-predictive-maintenance-in-industry-4-0/)
- [Recent advances in surface defect inspection of industrial products using deep learning techniques](https://scholariq.org/papers/recent-advances-in-surface-defect-inspection-of-industrial-products-using-deep/)
- [From knowledge-based to big data analytic model: a novel IoT and machine learning based decision support system for predictive maintenance in Industry 4.0](https://scholariq.org/papers/from-knowledge-based-to-big-data-analytic-model-a-novel-iot-and-machine-learning/)

## Topic primary papers

Showing 15 of 87.

- [2012 IEEE Conference on Computer Vision and Pattern Recognition](https://scholariq.org/papers/2012-ieee-conference-on-computer-vision-and-pattern-recognition/)
- [Deep learning for smart manufacturing: Methods and applications](https://scholariq.org/papers/deep-learning-for-smart-manufacturing-methods-and-applications/)
- [Machine learning in manufacturing: advantages, challenges, and applications](https://scholariq.org/papers/machine-learning-in-manufacturing-advantages-challenges-and-applications/)
- [Recent advances and trends in predictive manufacturing systems in big data environment](https://scholariq.org/papers/recent-advances-and-trends-in-predictive-manufacturing-systems-in-big-data/)
- [A Convolutional Neural Network for Fault Classification and Diagnosis in Semiconductor Manufacturing Processes](https://scholariq.org/papers/a-convolutional-neural-network-for-fault-classification-and-diagnosis-in/)
- [Convolutional Neural Network for Wafer Surface Defect Classification and the Detection of Unknown Defect Class](https://scholariq.org/papers/convolutional-neural-network-for-wafer-surface-defect-classification-and-the/)
- [Recent advances in surface defect inspection of industrial products using deep learning techniques](https://scholariq.org/papers/recent-advances-in-surface-defect-inspection-of-industrial-products-using-deep/)
- [From knowledge-based to big data analytic model: a novel IoT and machine learning based decision support system for predictive maintenance in Industry 4.0](https://scholariq.org/papers/from-knowledge-based-to-big-data-analytic-model-a-novel-iot-and-machine-learning/)
- [Multisensory fusion based virtual tool wear sensing for ubiquitous manufacturing](https://scholariq.org/papers/multisensory-fusion-based-virtual-tool-wear-sensing-for-ubiquitous-manufacturing/)
- [Deep Learning-Based Solar-Cell Manufacturing Defect Detection With Complementary Attention Network](https://scholariq.org/papers/deep-learning-based-solar-cell-manufacturing-defect-detection-with-complementary/)
- [PCB-YOLO: An Improved Detection Algorithm of PCB Surface Defects Based on YOLOv5](https://scholariq.org/papers/pcb-yolo-an-improved-detection-algorithm-of-pcb-surface-defects-based-on-yolov5/)
- [An Enhanced Memetic Differential Evolution in Filter Design for Defect Detection in Paper Production](https://scholariq.org/papers/an-enhanced-memetic-differential-evolution-in-filter-design-for-defect-detection/)
- [Adversarial Networks for Spatial Context-Aware Spectral Image Reconstruction from RGB](https://scholariq.org/papers/adversarial-networks-for-spatial-context-aware-spectral-image-reconstruction/)
- [A Deep Learning Model for Robust Wafer Fault Monitoring With Sensor Measurement Noise](https://scholariq.org/papers/a-deep-learning-model-for-robust-wafer-fault-monitoring-with-sensor-measurement/)
- [Transfer-Learning-Based Online Mura Defect Classification](https://scholariq.org/papers/transfer-learning-based-online-mura-defect-classification/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.