Light-programmed system projects 28-layer 3D images in single shot

Researchers at the UCLA Samueli School of Engineering and CNSI (California NanoSystems Institute), led by Professor Aydogan ...
IEEE

Long-Term Traffic Prediction Based on LSTM Encoder-Decoder Architecture

Abstract: Accurate traffic flow prediction is becoming increasingly important for transportation planning, control, management, and information services of successful. Numerous existing models focus ...
GitHub

180_LSTM_encoder_decoder_anomaly_GE.py

Shows errors on Tensorflow 1.4 and Keras 2.0.8 Works fine in Tensorflow: 2.2.0 Keras: 2.4.3 dataset: https://finance.yahoo.com/quote/GE/history/ Also try S&P: https ...
C&EN

A New Regularized Spatiotemporal Attention-Based LSTM with Application to Nitrogen Oxides Emission Prediction

State Key Laboratory of Process Automation in Mining and Metallurgy, Beijing 100160, China Beijing Key Laboratory of Process Automation in Mining and Metallurgy, Beijing 100160, China ...
Frontiers

Short-term load forecasting based on AM-CIF-LSTM method adopting transfer learning

Aiming at the unreliability of historical data for short-term load forecasting caused by the sudden change of power grid load under emergencies, a short-term load prediction method adopting transfer ...
Europe PMC

A hierarchical temporal attention-based LSTM encoder-decoder model for individual mobility prediction.

Prediction of individual mobility is crucial in human mobility related applications. Whereas, existing research on individual mobility prediction mainly focuses on next location prediction and ...