… 其主要思路包括利用生成对抗网络 (Generative Adversarial Networks, GAN)来实现不同 数据
… 数据输入到改进的卷积神经网络(Convolutional Neural Networks, CNN)中进行训练;或利用外部…

… data monitoring and anomaly detection techniques employing … and recurrent neural networks,
offer even more powerful … This enables data engineers and architects to understand data …

… the different standardized architecture of IoT systems and the … detection, anomaly detection,
Host-based IDS, and Network-… , IoT based hydroponics system using deep neural networks, …

… recurrent neural networks (RNNs) to capture both spatial and temporal features of fingerprint
images, improving the detection … -art convolutional neural network(CNN) architectures and …

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

… detect data anomalies from agricultural internet of things, one … anomaly detection. The
experiment was conducted … (Artificial intelligence)和深度学习(Deep learning)技术已广泛应用于图像…

… paper proposes an online anomaly detection framework with … 比如,有一些基于递归神经
网络(Recurrent Neural Network,RNN)… sequential Outlier detection with Deep Architectures,UODA)[…

… 卷积神经网络(convolutional neural networkꎬCNN)提取时间序列… -grained features; finally,
anomaly detection is carried out on the … Abnormal flow detection architecture for electric power …

… deep learning using convolutional neural network (CNN), which delivers exceptionally strong
performance for vision-based identification… in this study, various architectures are explored. …

… 循环神经网络(RNN,recurrent neural network),进一步提高了分类… in industrial internet of things
based on deep learning models[… sis technique for anomaly detection using trapezoidal area …