Autonomous Anomaly Detection Algorithm
The package contains:
1. AutonomusAnomalyDetection.m - The source code of the Autonomous Anomaly Detection algorithm;
2. demo.m - The demo
References:
[1] X. Gu, P. Angelov, “Autonomous anomaly detection”, in IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS), 2017, pp. 1-8.
[2] X. Gu, "Self-organising Transparent Learning System," Phd Thesis, Lancaster University, 2018.
This algorithm is an improved version [2] of the autonomous anomaly detection algorithm originally published in [1]. Please cite this algorithm using the above references if this code helps.
For any queries about the codes, please contact Prof. Plamen P. Angelov (p.angelov@lancaster.ac.uk) and Dr. Xiaowei Gu (x.gu3@lancaster.ac.uk)
Programmed by Xiaowei Gu
Zitieren als
X. Gu, P. Angelov, “Autonomous anomaly detection”, in IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS), 2017, pp. 1-8.
X. Gu, "Self-organising Transparent Learning System," Phd Thesis, Lancaster University, 2018.
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- Image Processing and Computer Vision > Computer Vision Toolbox > Point Cloud Processing > Display Point Clouds >
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Version | Veröffentlicht | Versionshinweise | |
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1.0.0.4 | The licence is updated. |
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1.0.0.3 | Updated References |
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1.0.0.2 | Updated Descriptions |
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1.0.0.1 | Changed Description |
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1.0.0 |