Update: 30 September, 2023
This paper introduces a deep learning based anomaly detection method. The method is able to effectively detect anomalies while maintaining the accuracy of normal data. The method first learns the distribution of normal data through a deep learning model. Then, the anomaly score of the data is calculated through statistical methods. Finally, the data is judged to be abnormal based on the threshold. Experimental results show that the method can effectively detect abnormal data and maintain the accuracy of normal data.
Brand: aprilia
File format: PDF
Size: 2322 KB
MD5 Checksum: D4D37878E91BFC31D0A81B9661C3D935
Publication date: 09 July, 2012
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PDF Link: aprilia 854006 ATLANTIC 250 i.e. F-E 2006 Manual PDF