Thus, we first used the autoencoder network, to roughly screen out the features to a proper dimension. The detailed two-stepwise feature selection procedure is described as follows: Step 1: We trained ...

Electrocardiograms (ECG) are vital for diagnosing various cardiac conditions but are often corrupted by noise from multiple sources, which can hinder accurate interpretation. Denoising ECG signals is ...

In the last decade, automatic writer identification using a convolutional neural network (CNN) has been well studied. For further performance improvement of the writer identification task, a ...

In this study, k-means clustering was performed on the data set using raw data and PCA-extracted and deep autoencoder-extracted features.The performance of the clusters was compared between each input ...

Train the autoencoder model on normal data and use it to detect anomalies in test data. Utilize the pattern detection rules to analyze transaction patterns for fraud detection. Future Improvements: ...

Fanai, H. and Abbasimehr, H. (2023) A Novel Combined Approach Based on Deep Autoencoder and Deep Classifiers for Credit Card Fraud Detection. Expert Systems with Applications, 217, Article ID 119562.