… His research interest covers deep learning and anomaly detection … -based online detection
approach on the perspective of temporal anomaly detection. First, a new deep auto-encoder …

… anomaly detection methods and the applicability when applied to security protection of the
industrial Internet of things (… An ensemble of deep recurrent neural networks for detecting IoT …

… suggested a non-parametric outlier detection (NPOD) model for … bigger visualization of IoT
(exercise intensity increases-IoT) to … In this area, we examine distributed computing, enormous …

… Detection of forest fire using Artificial Neural Network (ANN) … The use of the Internet of Things
(IoT) for the detection of forest fire … a combination of data classification and outlier detection …

… agricultural data based on broad convolution neural network[J]… detect data anomalies from
agricultural internet of things, … and trained for conducting anomaly detection. The experiment …

… is proposed and used for anomaly detection, named sample-… 建模,利用图神经网络(Graph
neural network, GNN)对数据的关联… for Sybil attack under mobile RPL in the Internet of things. …

… deep learning techniques, particularly convolutional neural networks (… to ensure that each
set contains a representative distribution … , graph neural networks, and self-supervised learning …

… of the Internet of things, so that the objects of the Internet of things can … method of intrusion
detection based on anomaly detection … Anomaly detection using graph neural networks[C]//…

… Chen XL (2013) An Approach to scenario construction and dynamic scenario deduction
of … by a back propapagtion neural network. J Tsinghua Univ (Sci Technol) 55 (12): 1342–1347 …

… of distributed photovoltaic, a Quantile Regression Neural … A quantile regression neural
network approach to estimating … Hierarchical anomaly detection and multimodal classification in …