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Found 5 papers, 2 papers with code
Learning Dual-Pixel Alignment for Defocus Deblurring
Generally, DPANet is an encoder-decoder with skip-connections, where two branches with shared parameters in the encoder are employed to extract and align deep features from left and right views, and one decoder is adopted to fuse aligned features for predicting the sharp image.
Weakly Supervised Arrhythmia Detection Based on Deep Convolutional Neural Network
The results show that the models achieve beat-level accuracies of 99. 09% in detecting atrial fibrillation, and 99. 13% in detecting morphological arrhythmias, which are comparable to that of fully supervised learning models, demonstrating their effectiveness.
Two-Stage Single Image Reflection Removal with Reflection-Aware Guidance
To be specific, the reflection layer is firstly estimated due to that it generally is much simpler and is relatively easier to estimate.
Automatic Detection of ECG Abnormalities by using an Ensemble of Deep Residual Networks with Attention
Heart disease is one of the most common diseases causing morbidity and mortality.
Automatic Detection of Atrial Fibrillation Based on Continuous Wavelet Transform and 2D Convolutional Neural Networks
The proposed method analyzed the time-frequency features of the electrocardiogram (ECG), thus being different to conventional AF detecting methods that implement isolating atrial or ventricular activities.
Ranked #2 on
Atrial Fibrillation Detection
on MIT-BIH AF
