Tag: CNN

A hybrid deep learning model combining CNN and bidirectional LSTM networks can identify MOOC students at risk of dropping out ...

A hybrid deep learning framework called HLnet combines CNN frequency decomposition with Transformer attention to synthesize T1- and T2-weighted MRI ...

Schizophrenia and bipolar disorder have haunted psychiatry with a diagnostic dilemma that is as old as the disciplines themselves. Both ...

A hybrid CNN–BiLSTM network with additive attention classifies brain MRI into four Alzheimer's disease stages with 95.94% slice-level accuracy, while ...

A systematic review of 83 studies finds that while deep learning models excel at ECG-based cardiovascular disease prediction, weak external ...

A systematic review and controlled validation of deep learning-based Android malware detection reveals that high benchmark accuracy masks architecture-dependent reliability ...

A hybrid CNN-BiLSTM model with multi-head self-attention classifies five EEG brain states, including seizures, with 98.83 percent accuracy on a ...

A new parallel Transformer-CNN architecture called TCNNISTD achieves state-of-the-art accuracy and real-time speed in detecting infrared targets smaller than ten ...

Korean researchers have built a hybrid Vision Transformer and CNN generative model that enhances ultrasound image quality with state-of-the-art fidelity ...

Researchers have developed a CNN-BiLSTM-Attention hybrid neural network optimized by an improved antlion algorithm that diagnoses and predicts transformer faults ...