Anomaly Detection Techniques and Applications
Anomaly Detection Techniques and Applications is a research topic within Artificial Intelligence. Science Explorer counts 55k research works in it since 1950. 22.1% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the detection of anomalies in high-dimensional data, particularly in the context of video analysis, surveillance, and time series data. It covers a wide range of techniques including unsupervised learning, outlier detection, deep learning, and novelty detection for identifying abnormal patterns and events.
- Anomaly Detection
- Unsupervised
- Outlier Detection
- Deep Learning
- High-Dimensional Data
- Video Analysis
- Neural Networks
- Novelty Detection
- Surveillance
- Time Series
- Research works
- 55k fractional, since 1950
- In the world top 10%
- 12k per year above
- Top-10% rate
- 22.1% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +171% the tick is no change
Which countries lead Anomaly Detection Techniques and Applications research?
By volume, China and India publish the most (8.6k and 3.4k works in 2022–2025).
By volume, 2022–2025
- 1 China 8.6k works
- 2 India 3.4k works
- 3 United States 2.6k works
- 4 South Korea 686 works
- 5 Germany 677 works
- 6 United Kingdom 603 works
- 7 Italy 526 works
- 8 Japan 517 works
- 9 Canada 430 works
- 10 France 428 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 Anomaly Detection Techniques and Applications research?
By volume in 2022–2025, Tsinghua University publishes the most Anomaly Detection Techniques and Applications research, followed by Beijing University of Posts and Telecommunications and National University of Defense Technology.
By volume, 2022–2025
- 1 Tsinghua UniversityChina 129 works
- 2 Beijing University of Posts and TelecommunicationsChina 125 works
- 3 National University of Defense TechnologyChina 123 works
- 4 SRM Institute of Science and TechnologyIndia 123 works
- 5 Beihang UniversityChina 117 works
- 6 University of Electronic Science and Technology of ChinaChina 113 works
- 7 Harbin Institute of TechnologyChina 113 works
- 8 Xi'an Jiaotong UniversityChina 112 works
- 9 Chinese Academy of SciencesChina 111 works
- 10 Vellore Institute of Technology UniversityIndia 111 works
Who are the leading researchers in Anomaly Detection Techniques and Applications?
The most-cited researchers publishing on Anomaly Detection Techniques and Applications include Andrew Zisserman, Li Fei-Fei and Yoshua Bengio.
- 1 Andrew Zisserman United Kingdom 25k citations
- 2 Li Fei-Fei United States 17k citations
- 3 Yoshua Bengio Canada 17k citations
- 4 Serge Belongie United States 14k citations
- 5 Xiaogang Wang Russia 13k citations
- 6 Jitendra Malik United States 12k citations
- 7 Deva Ramanan United States 11k citations
- 8 Wei Liu China 9.7k citations
- 9 Luc Van Gool Switzerland 8.5k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Anomaly Detection Techniques and Applications research done?
The largest centres of Anomaly Detection Techniques and Applications research in 2022–2025 are Beijing (China), Shanghai (China), Xi'an (China) and Nanjing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Vijayawada.
Largest cities, 2022–2025
Where it is the local speciality
- VijayawadaIN · 69.6 works6.3×
Location quotient: how much more of its research is in Anomaly Detection Techniques and Applications than the world average.
Where is the best place to study Anomaly Detection Techniques and Applications?
Among universities, judged by research, Mohamed bin Zayed University of Artificial Intelligence, Air University and Singapore Management University 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 | Mohamed bin Zayed University of Artificial IntelligenceUnited Arab Emirates | 67.1 | 42.1% | 13.4× | 13 | — |
| 2 | Air UniversityPakistan | 65.8 | 45.0% | 10.8× | 15 | — |
| 3 | Singapore Management UniversitySingapore | 65.1 | 41.2% | 6.5× | 17 | +201.0% |
| 4 | Beijing University of Posts and TelecommunicationsChina | 64.4 | 17.0% | 8.5× | 125 | +161.6% |
| 5 | King Abdulaziz UniversitySaudi Arabia | 63.3 | 48.7% | 2.2× | 29 | +242.6% |
| 6 | Sejong UniversitySouth Korea | 63.3 | 45.7% | 4.5× | 20 | +309.7% |
| 7 | North Carolina Agricultural and Technical State UniversityUnited States | 58.3 | 47.0% | 6.5× | 13 | +127.3% |
| 8 | Beihang UniversityChina | 57.7 | 30.0% | 4.4× | 117 | +92.0% |
| 9 | Vellore Institute of Technology UniversityIndia | 57.3 | 19.3% | 4.7× | 111 | +623.2% |
| 10 | Xidian UniversityChina | 57.0 | 28.0% | 5.5× | 96 | +84.0% |
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 Anomaly Detection Techniques and Applications research growing?
Output in 2018–2022 was 171% higher than in 2013–2017, peaking in 2024. The fastest-growing topics are Anomaly Detection Techniques and Applications.
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.