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Algorithm maps the connections between the brain's structure and function
Using an algorithm they call the Krakencoder, researchers at Weill Cornell Medicine are a step closer to unraveling how the ...
GitHub17d
Aikhusy/Progress-LSTM-AUTOENCODER
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 ...
GitHub14d
Prometheus Time Series Anomaly Detection with LSTM Autoencoder
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 ...
IEEE27d
LSTM-Autoencoder For Faster-Than-Nyquist Optical Wireless MIMO Communication System
To address this issue, an end-to-end (E2E) FTN-MIMO OWC system utilizing a long short-term memory (LSTM) autoencoder has been proposed. This approach effectively eliminates the influence of ISI and ...
Scientific Research Publishing17d
Harvey, C.J., Shomaji, S., Yao, Z. and Noheria, A. (2024) Comparison of Autoencoder Encodings for ECG Representation in Downstream Prediction Tasks. arXiv: 2410.02937.
ABSTRACT: The rapid growth of unlabeled time-series data in domains such as wireless communications, radar, biomedical engineering, and the Internet of Things (IoT) has driven advancements in ...
Frontiers22d
Integrating multi-source monitoring data and deep convolutional autoencoder technology for slope failure pattern recognition
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 ...