Tag: LSTM

A contactless deep learning framework estimated window-averaged zygomaticus major sEMG envelope amplitude from facial video with a mean correlation of ...

Three tiny neural networks, each under 50,000 parameters, cut prediction error by more than half and reached up to 95 ...

A deep learning framework that fuses construction schedules with wall-deflection monitoring data cut long-term prediction errors for diaphragm walls at ...

A graph convolutional network with incremental learning improves network anomaly detection across three benchmark datasets by adapting to evolving attack ...

A hybrid VMD-CBiLSTM model optimized by the shuffled frog-leaping algorithm achieved an average R2 of 0.981 when predicting PM2.5 concentrations ...

A new deep learning model combining wavelet decomposition, a CNN and LSTM layers achieved an RMSE of 0.09 in forecasting ...

A new two-layer hypergraph model simulates opinion change and workplace switching, with LSTM and XGBoost performing best at estimating its ...

A landmark head-to-head study finds that a YOLOv3 image detector outperforms point-cloud-native and modular machine learning methods for detecting moving ...

A new open access study proposes a four-layer framework combining machine learning forecasting, uncertainty-aware optimization, and automated fault redispatch for ...

A hybrid LSTM and CNN model outperformed traditional time series and individual machine learning models in predicting monthly hepatitis B ...

A newly published study in Discover Artificial Intelligence proposes a machine learning framework designed specifically for this problem, combining a ...

A multi-model NLP study of more than 200 online cancer narrative sources found negative sentiment dominated diagnosis and treatment discourse, ...

Researchers have built an explainable stacking machine learning framework that jointly forecasts electrical load and predicts transformer remaining lifespan in ...

A replication and extension study in Cluster Computing confirms that LSTM networks maintain high intrusion detection performance in IoT networks, ...

A simulation study presents an ISO 26262-inspired multi-layer safety architecture for powered two-wheelers that achieved 88 percent collision detection and ...

A systematic review of 78 papers examines how machine learning methods support demand forecasting and inventory decision-making.

A hybrid SEIR–LSTM framework applied to 1,401 days of Sierra Leone COVID-19 surveillance data found the plain mechanistic model outperformed ...

A study of 1,000 university learners identified four distinct online English learning behavior patterns and showed that feeding them into ...

A new attention-based neural network that reconfigures its risk logic according to macroeconomic conditions outperformed standard machine learning and statistical ...

Researchers have built a federated, explainable deep learning framework that detects attacks on Internet of Medical Things devices with detection ...