Treasury Secretary Scott Bessent said Monday he believes the Federal Reserve system should be reviewed for potentially ...

This study proposes a rolling bearing fault diagnosis model called CNN-BiLSTM-SE, which integrates Convolutional Neural Networks (CNN), Bidirectional Long Short-Term Memory Networks (BiLSTM), and ...

Advanced Persistent Threat (APT) is a highly targeted, complex, and long-term attack targeting specific organizations or individuals, aimed at stealing sensitive data or disrupting operations. APT is ...

We perform extensive experiments on standard structural picture datasets to showcase the efficacy of our suggested methodology. The findings demonstrate that our hybrid CNN-GNN model surpasses current ...

Extracting effective features is always a challenging problem for texture classification because of the uncertainty of scales and the clutter of textural patterns. For texture classification, spectral ...

This research work provides a comprehensive research study of CNN-SVM based techniques for the classification of dermatological diseases. It discusses key aspects such as dataset preparation, model ...

The paper introduces a novel convolutional neural network (CNN) model called "CNN model", which is specifically designed to classify and detect red dots using skin images. A dataset containing 3,192 ...

The CNN-RF method is based on Convolutional Neural Networks (CNNs) feature extraction and classification provided by Random Forests (RFs). Based on the results of the experiments, it was established ...

Portfolio theory underpins portfolio management, a much-researched yet uncharted field. This research suggests a collective framework combined with the essence of deep learning for stock selection ...

The aim of the work is to design a secure and accurate Speech Emotion Recognition (SER) system using a RNN model to classify emotions from speech data. The system’s predictive accuracy is evaluated ...

Early and accurate detection of skin cancer, particularly melanoma, is critical for improving survival rates and treatment outcomes. This study introduces SkinScanNet, a CNN-based deep learning model ...

Coronary Heart Disease popularly referred to as CHD is one of the leading causes of death and illness across the global population making it imperative for the identification of an effective approach ...