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Anomaly Detection Techniques and Applications
TopicLeading institutions, researchers & key papers
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.
286
Works
IDs:OpenAlex
How has Anomaly Detection Techniques and Applications's publication output changed over time?
ScholarIQpublication output · 2005–2022
Output grew200% over the shown period — from 1 works in 2005 to 3 in 2022.
1
1
1
1
1
2
1
4
3
200520142016201720182019202020212022
What are the most-cited papers on Anomaly Detection Techniques and Applications?
ScholarIQmost cited works
Anomaly Detection via Reverse Distillation from One-Class Embedding
Hanqiu Deng, Xingyu Li
S4363607701. 2022759 Citations
A survey on machine learning for data fusion
Tong Meng, Xuyang Jing, Zheng Yan, Witold Pedrycz
S7560371. 2019657 CitationsOPEN ACCESS
Recent advances in convolutional neural network acceleration
Qianru Zhang, Meng Zhang, Tinghuan Chen, Zhifei Sun, Yuzhe Ma, Bei Yu
S45693802. 2018433 Citations
A Review on Machine Learning Styles in Computer Vision—Techniques and Future Directions
Supriya V. Mahadevkar, Bharti Khemani, Shruti Patil, Ketan Kotecha, Deepali Vora, Ajith Abraham, Lubna A. Gabralla
IEEE Access. 2022281 CitationsOPEN ACCESS
An intelligent emergency response system: preliminary development and testing of automated fall detection
Tracy Lee, Alex Mihailidis
S63600306. 2005235 Citations
Where is Anomaly Detection Techniques and Applications research published, and who funds it?
ScholarIQvenues & funding sources
TOP JOURNALS
TOP FUNDERS
National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
Funder breakdown is a member featureSign up free to unlock
How much of the research on Anomaly Detection Techniques and Applications is open access?
ScholarIQopen access share
33%OPEN ACCESS
Gold
13%
Green
20%
Hybrid
0%
Bronze
0%
Closed
67%
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