no code implementations • 19 May 2021 • Ming-Chang Lee, Jia-Chun Lin, Ernst Gunnar Gran
Otherwise, DistTune customizes an LSTM model for the detector to achieve fine-grained prediction.
no code implementations • 19 Apr 2021 • Ming-Chang Lee, Jia-Chun Lin, Ernst Gunnar Gran
If the difference between a calculated AARE value and its corresponding forecast AARE value is higher than a self-adaptive detection threshold, the corresponding data point is considered anomalous.
no code implementations • 12 Feb 2021 • Ming-Chang Lee, Jia-Chun Lin, Ernst Gunnar Gran
Anomaly detection is the process of identifying unexpected events or ab-normalities in data, and it has been applied in many different areas such as system monitoring, fraud detection, healthcare, intrusion detection, etc.
no code implementations • 10 May 2020 • Ming-Chang Lee, Jia-Chun Lin, Ernst Gunnar Gran
To make such customization process efficient and applicable for large-scale transportation networks, DistPre conducts LSTM customization on a cluster of computation nodes and allows any trained LSTM model to be shared between different detectors.
no code implementations • 5 Apr 2020 • Ming-Chang Lee, Jia-Chun Lin, Ernst Gunnar Gran
Anomaly detection is an active research topic in many different fields such as intrusion detection, network monitoring, system health monitoring, IoT healthcare, etc.
no code implementations • 24 Jan 2020 • Ming-Chang Lee, Jia-Chun Lin, Ernst Gunnar Gran
Providing real-time and proactive anomaly detection for streaming time series without human intervention and domain knowledge is highly valuable since it greatly reduces human effort and enables appropriate countermeasures to be undertaken before a disastrous damage, failure, or other harmful event occurs.