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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Generative Adversarial Active Learning for Unsupervised Outlier Detection
Yezheng Liu, Zhe Li, Chong Zhou, et al.
IEEE Transactions on Knowledge and Data Engineering (2019), pp. 1-1
Open Access | Times Cited: 296

Showing 1-25 of 296 citing articles:

Deep Learning for Anomaly Detection
Guansong Pang, Chunhua Shen, Longbing Cao, et al.
ACM Computing Surveys (2021) Vol. 54, Iss. 2, pp. 1-38
Open Access | Times Cited: 1535
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications
Jie Gui, Zhenan Sun, Yonggang Wen, et al.
IEEE Transactions on Knowledge and Data Engineering (2021) Vol. 35, Iss. 4, pp. 3313-3332
Open Access | Times Cited: 765
Progress in Outlier Detection Techniques: A Survey
Hongzhi Wang, Mohamed Jaward Bah, Mohamed Hammad
IEEE Access (2019) Vol. 7, pp. 107964-108000
Open Access | Times Cited: 426
COPOD: Copula-Based Outlier Detection
Zheng Li, Yue Zhao, Nicola Botta, et al.
2021 IEEE International Conference on Data Mining (ICDM) (2020), pp. 1118-1123
Open Access | Times Cited: 261
Ensemble unsupervised autoencoders and Gaussian mixture model for cyberattack detection
Peng An, Zhiyuan Wang, Chunjiong Zhang
Information Processing & Management (2022) Vol. 59, Iss. 2, pp. 102844-102844
Closed Access | Times Cited: 209
A comprehensive review on deep learning-based methods for video anomaly detection
Rashmiranjan Nayak, Umesh Chandra Pati, Santos Kumar Das
Image and Vision Computing (2020) Vol. 106, pp. 104078-104078
Closed Access | Times Cited: 208
ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions
Zheng Li, Yue Zhao, Xiyang Hu, et al.
IEEE Transactions on Knowledge and Data Engineering (2022) Vol. 35, Iss. 12, pp. 12181-12193
Open Access | Times Cited: 199
Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure
Fuli Feng, Xiangnan He, Jie Tang, et al.
IEEE Transactions on Knowledge and Data Engineering (2019) Vol. 33, Iss. 6, pp. 2493-2504
Closed Access | Times Cited: 177
TSMAE: A Novel Anomaly Detection Approach for Internet of Things Time Series Data Using Memory-Augmented Autoencoder
Honghao Gao, Binyang Qiu, Ramón J. Durán Barroso, et al.
IEEE Transactions on Network Science and Engineering (2022) Vol. 10, Iss. 5, pp. 2978-2990
Closed Access | Times Cited: 159
Discriminative Reconstruction Constrained Generative Adversarial Network for Hyperspectral Anomaly Detection
Tao Jiang, Yunsong Li, Weiying Xie, et al.
IEEE Transactions on Geoscience and Remote Sensing (2020) Vol. 58, Iss. 7, pp. 4666-4679
Closed Access | Times Cited: 155
Improving the Reliability of Deep Neural Networks in NLP: A Review
Basemah Alshemali, Jugal Kalita
Knowledge-Based Systems (2019) Vol. 191, pp. 105210-105210
Closed Access | Times Cited: 153
Mean-shift outlier detection and filtering
Jiawei Yang, Susanto Rahardja, Pasi Fränti
Pattern Recognition (2021) Vol. 115, pp. 107874-107874
Open Access | Times Cited: 122
OpenGAN: Open-Set Recognition via Open Data Generation
Shu Kong, Deva Ramanan
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2021)
Open Access | Times Cited: 122
Semi-supervised anomaly detection algorithms: A comparative summary and future research directions
Miryam Elizabeth Villa-Pérez, Miguel Á. Álvarez‐Carmona, Octavio Loyola‐González, et al.
Knowledge-Based Systems (2021) Vol. 218, pp. 106878-106878
Closed Access | Times Cited: 104
Spatio-Temporal Feature Encoding for Traffic Accident Detection in VANET Environment
Zhili Zhou, Xiaohua Dong, Zhetao Li, et al.
IEEE Transactions on Intelligent Transportation Systems (2022) Vol. 23, Iss. 10, pp. 19772-19781
Closed Access | Times Cited: 98
Effectively Detecting Operational Anomalies In Large-Scale IoT Data Infrastructures By Using A GAN-Based Predictive Model
Peng Chen, Hongyun Liu, Ruyue Xin, et al.
The Computer Journal (2022) Vol. 65, Iss. 11, pp. 2909-2925
Closed Access | Times Cited: 97
LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks
Adam Goodge, Bryan Hooi, See-Kiong Ng, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2022) Vol. 36, Iss. 6, pp. 6737-6745
Open Access | Times Cited: 72
Outlier detection using iterative adaptive mini-minimum spanning tree generation with applications on medical data
Jia Li, Jiangwei Li, Chenxu Wang, et al.
Frontiers in Physiology (2023) Vol. 14
Open Access | Times Cited: 43
Systematic ensemble model selection approach for educational data mining
MohammadNoor Injadat, Abdallah Moubayed, Ali Bou Nassif, et al.
Knowledge-Based Systems (2020) Vol. 200, pp. 105992-105992
Open Access | Times Cited: 128
adVAE: A self-adversarial variational autoencoder with Gaussian anomaly prior knowledge for anomaly detection
Xuhong Wang, Ying Du, Shijie Lin, et al.
Knowledge-Based Systems (2019) Vol. 190, pp. 105187-105187
Open Access | Times Cited: 98
One-class graph neural networks for anomaly detection in attributed networks
Xuhong Wang, Baihong Jin, Ying Du, et al.
Neural Computing and Applications (2021) Vol. 33, Iss. 18, pp. 12073-12085
Closed Access | Times Cited: 86
Applications of Generative Adversarial Networks in Anomaly Detection: A Systematic Literature Review
Mikael Sabuhi, Ming Zhou, Cor‐Paul Bezemer, et al.
IEEE Access (2021) Vol. 9, pp. 161003-161029
Open Access | Times Cited: 70
Deep anomaly detection with self-supervised learning and adversarial training
Xianchao Zhang, Jie Mu, Xiaotong Zhang, et al.
Pattern Recognition (2021) Vol. 121, pp. 108234-108234
Closed Access | Times Cited: 69
Efficient density and cluster based incremental outlier detection in data streams
Ali Değırmencı, Ömer Karal
Information Sciences (2022) Vol. 607, pp. 901-920
Closed Access | Times Cited: 61
Review on Deep Learning Approaches for Anomaly Event Detection in Video Surveillance
Sabah Abdulazeez Jebur, Khalid Ali Hussein, Haider K. Hoomod, et al.
Electronics (2022) Vol. 12, Iss. 1, pp. 29-29
Open Access | Times Cited: 45
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