First, to reduce the distance between multi-source homogeneous signals in the feature space, we design a novel Contrastive Pairs AutoEncoder (CPAE), which is for feature alignment before aggregating ...

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 ...

The proposed MVJSCC adopts a lightweight autoencoder structure integrated with OFDM transmission, achieving adaptation through a lightweight efficient channel attention (ECA) based channel adaptation ...

fw_load_avg_1_min fw_load_avg_5_min fw_load_avg_15_min fw_cpu_used mem_used root_used log_used fw_total_alloc model saya menemukan bahwa [31, 34, 47, 48, 49, 50, 51 ...

The geological structure of this section is significantly influenced ... Figure 5. Model architecture diagram of the deep convolutional autoencoder. The input to the model is a 9 × 24 matrix, where 9 ...