Industrial Vision Systems and Defect Detection
Industrial Vision Systems and Defect Detection is a research topic within Industrial and Manufacturing Engineering. Science Explorer counts 48k research works in it since 1950. 12.3% of them reached the world's top 10% most cited for their field and year.
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.
- Fabric Defect Detection
- Machine Vision
- Texture Analysis
- Semiconductor Manufacturing
- Deep Learning
- Wafer Map Defect Classification
- Gabor Filters
- Automated Inspection
- Surface Defect Detection
- Virtual Metrology
- Research works
- 48k fractional, since 1950
- In the world top 10%
- 5.9k per year above
- Top-10% rate
- 12.3% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +79% the tick is no change
Which countries lead Industrial Vision Systems and Defect Detection research?
By volume, China and India publish the most (7.9k and 1.3k works in 2022–2025).
By volume, 2022–2025
- 1 China 7.9k works
- 2 India 1.3k works
- 3 United States 1.2k works
- 4 Germany 535 works
- 5 South Korea 513 works
- 6 Japan 497 works
- 7 Taiwan 379 works
- 8 United Kingdom 301 works
- 9 Indonesia 288 works
- 10 Türkiye 269 works
How concentrated that is
The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.
Shares of the rows listed above, not of the whole node.
Which institutions lead Industrial Vision Systems and Defect Detection research?
By volume in 2022–2025, Northeastern University publishes the most Industrial Vision Systems and Defect Detection research, followed by Huazhong University of Science and Technology and Zhejiang University.
By volume, 2022–2025
- 1 Northeastern UniversityChina 92 works
- 2 Huazhong University of Science and TechnologyChina 92 works
- 3 Zhejiang UniversityChina 86 works
- 4 Shanghai Jiao Tong UniversityChina 84 works
- 5 Tsinghua UniversityChina 81 works
- 6 Beihang UniversityChina 79 works
- 7 Xi'an Jiaotong UniversityChina 78 works
- 8 Wuhan University of TechnologyChina 73 works
- 9 Harbin Institute of TechnologyChina 71 works
- 10 Southeast UniversityChina 69 works
Who are the leading researchers in Industrial Vision Systems and Defect Detection?
The most-cited researchers publishing on Industrial Vision Systems and Defect Detection include Andrew Zisserman, Luc Van Gool and Thomas S. Huang.
- 1 Andrew Zisserman United Kingdom 25k citations
- 2 Luc Van Gool Switzerland 8.5k citations
- 3 Thomas S. Huang United States 7.4k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Industrial Vision Systems and Defect Detection research done?
The largest centres of Industrial Vision Systems and Defect Detection research in 2022–2025 are Beijing (China), Shanghai (China), Xi'an (China) and Wuhan (China). Among places with at least 20 works in it, it is an unusually large share of all research in Jinrongjie, Douliu and Zigong.
Largest cities, 2022–2025
Where it is the local speciality
- JinrongjieCN · 31.8 works23×
- DouliuTW · 21.5 works11×
- ZigongCN · 27.9 works11×
Location quotient: how much more of its research is in Industrial Vision Systems and Defect Detection than the world average.
Where is the best place to study Industrial Vision Systems and Defect Detection?
Among universities, judged by research, Zhejiang Sci-Tech University, Northeastern University and University of Huddersfield score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Zhejiang Sci-Tech UniversityChina | 58.2 | 25.9% | 10.8× | 53 | -61.8% |
| 2 | Northeastern UniversityChina | 56.3 | 27.1% | 6.5× | 92 | -18.4% |
| 3 | University of HuddersfieldUnited Kingdom | 53.6 | 47.9% | 4.8× | 8 | — |
| 4 | Shanghai University of Engineering ScienceChina | 53.4 | 12.0% | 9.5× | 37 | +91.3% |
| 5 | Tianjin University of Technology and EducationChina | 53.3 | 10.6% | 20.1× | 25 | +156.0% |
| 6 | Shanghai Institute of TechnologyChina | 52.9 | 7.4% | 11.4× | 30 | +150.8% |
| 7 | Hong Kong Polytechnic UniversityHong Kong | 52.1 | 41.6% | 2.2× | 30 | -29.3% |
| 8 | Wuhan University of Science and TechnologyChina | 50.9 | 18.4% | 8.0× | 43 | +26.8% |
| 9 | National Taipei University of TechnologyTaiwan | 50.2 | 14.8% | 9.2× | 23 | +45.4% |
| 10 | Nanyang Technological UniversitySingapore | 50.1 | 20.7% | 2.1× | 27 | +191.2% |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Industrial Vision Systems and Defect Detection research growing?
Output in 2018–2022 was 79% higher than in 2013–2017, peaking in 2024. The fastest-growing topics are Industrial Vision Systems and Defect Detection.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Which topics inside it are moving
Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.