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Found 6 papers, 2 papers with code
An EMD-based Method for the Detection of Power Transformer Faults with a Hierarchical Ensemble Classifier
In this paper, an Empirical Mode Decomposition-based method is proposed for the detection of transformer faults from Dissolve gas analysis (DGA) data.
Power Transformer Fault Diagnosis with Intrinsic Time-scale Decomposition and XGBoost Classifier
The proposed method's performance in classification is studied using publicly available DGA data of 376 power transformers and employing an XGBoost classifier.
Weighted Contourlet Parametric (WCP) Feature Based Breast Tumor Classification from B-Mode Ultrasound Image
Specifically, with the support vector machine and k-nearest-neighbor classifier, very high accuracies of 97. 2% and 97. 55% can be obtained for the Mendeley Data and Dataset B, respectively, using the weighted contourlet parametric images. The reported classification performance is also compared with that of other works using the datasets employed in this paper.
A Lightweight CNN Model for Detecting Respiratory Diseases from Lung Auscultation Sounds using EMD-CWT-based Hybrid Scalogram
Listening to lung sounds through auscultation is vital in examining the respiratory system for abnormalities.
X-Ray Image Compression Using Convolutional Recurrent Neural Networks
To the best of our knowledge, this is the first reported evaluation on using a deep convolutional RNN for medical image compression.
End-to-end Sleep Staging with Raw Single Channel EEG using Deep Residual ConvNets
The experimental results demonstrate the superiority of the proposed network compared to the best existing method, providing a relative improvement in epoch-wise average accuracy of 6. 8% and 6. 3% on the household data and multi-source data, respectively.
