This paper introduces GeneA-SLAM2, an RGB-D SLAM system for dynamic environments. It eliminates dynamic object interference via depth statistical information and enhances keypoint distribution ...

It uses an LSTM (Long Short-Term Memory) autoencoder model built with TensorFlow/Keras to learn normal patterns from your metrics and identify deviations. The system includes scripts for data ...

As a typical deep network, stacked autoencoder (SAE) has an outstanding modeling capability in soft sensors due to its ability to extract deep features. However, SAE ignores the expanded ...

In recent years, data-driven soft sensors, especially deep learning soft sensors show great potential for application in the process industry. As a typical deep network, stacked autoencoder (SAE) has ...