LSTM Dynamic Autoencoder Reaches 97 Percent Accuracy in Sequential Data Clustering
A new LSTM-based dynamic autoencoder achieves up to 97 percent accuracy on benchmark sequential datasets by mitigating feature instability.
Tag: reconstruction loss
Dual Autoencoder and SVDD Architecture Accurately Detects Complex Industrial Anomalies
Researchers have demonstrated an unsupervised industrial anomaly detection framework that integrates autoencoder reconstruction loss and support vector data description boundary ...
