An Attention-Based Deep Sequential GRU Model for Sensor Drift Compensation
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DOI: 10.1109/jsen.2020.3044388
Abstract: Sensor accuracy is vital for the reliability of sensing applications. However, sensor drift is a common problem that leads to inaccurate measurement readings. Owing to aging and environmental variation, chemical gas sensors in particular are… read more here.
Keywords: gru; attention; model; drift ... See more keywords
EdgeLSTM: Towards Deep and Sequential Edge Computing for IoT Applications
Sign Up to like & getrecommendations! Published in 2021 at "IEEE/ACM Transactions on Networking"
DOI: 10.1109/tnet.2021.3075468
Abstract: The time series data generated by massive sensors in Internet of Things (IoT) is extremely dynamic, heterogeneous, large scale and time-dependent. It poses great challenges (e.g. accuracy, reliability, stability) on the real-time analysis and decision… read more here.
Keywords: iot applications; time; time series; deep sequential ... See more keywords