IEEE

Enhanced Seizure Prediction Using XGBoost and EEG Data: A Machine Learning Approach with increasing Model Metrics

Abstract: Epilepsy is a neurological disorder marked by abnormal brain activity. Normally, brain cells (neurons) communicate with each other through electrical signals. In epilepsy, these signals ...
IEEE

Rolling Bearing Fault Diagnosis Based on VMD-CNN-SLSTM Model

Abstract: Convolutional neural networks (CNN) are limited by the local receptive field, making it difficult to capture the shock features of the cross period. In view of this limitation, a ...
IEEE

Characterization of Cortical Connectivity in the Deception State With a Data-Driven Network Model Based on EEG Signal

Abstract: This study investigates the pattern of information interaction at the cortical level during deception, aiming to reveal the cognitive processes involved in the deception task. Our study ...
IEEE

Enhancing Sleep Stage Classification With Single Channel EEG: Feature Extraction and Random Forest-XGBoost Model

Abstract: Sleep stage classification, essential for diagnosing sleep disorders, monitoring neurological health, and advancing cognitive neuroscience. Traditionally involves manual scoring of ...
IEEE

LSTA-CNN: A Lightweight Spatiotemporal Attention-Based Convolutional Neural Network for ASD Diagnosis Using EEG

Abstract: Electroencephalography (EEG) is an effective assessment tool to identify autism spectrum disorders with low cost, and deep learning has been applied in EEG analysis for extracting meaningful ...
IEEE

A Hybrid CNN-LSTM Deep Learning Model for Next-Generation OFDM Channel Estimation in Wireless Networks

Abstract: Orthogonal Frequency Division Multiplexing (OFDM) enables high-rate data transmission wards wirelss broadband connections. Accurate channel estimation continues to be an unsolved issue in ...
IEEE

Emotion Recognition from EEG Signals Using Vision Transformer and CNN

Abstract: Emotional expression and interaction are fundamental aspects of daily life. Understanding emotions not only improves communication but also offers significant potential for medical ...
IEEE

Joint estimation of DOA and polarization parameters based on CNN-Transformer hybrid architecture

Abstract: Compared with traditional scalar arrays, polarization-sensitive arrays can simultaneously obtain spatial domain information and polarization information.So it has stronger anti-interference ...
IEEE

Mutual Information Disentanglement Based Domain Adaptation Model for EEG Emotion Recognition

Abstract: To address the lack of generalized feature representation in cross-domain electroencephalogram emotion recognition, this letter proposes a multi-source domain adaptation model that ...
IEEE

Hybrid CNN–LGBM Model for Planetary Boundary Layer Height Estimation Combined With Temporal–Height–Spatial Features

Abstract: The planetary boundary layer (PBL) height (PBLH), as a critical meteorological parameter, plays a pivotal role in atmospheric dynamics, climate, and pollution diffusion studies. A radar wind ...
IEEE

Enhancing Result Interpretability of Neural Architecture Search-Assisted Medical AI via Large Language Model

Abstract: NAS can find better solutions by exploring the vast search space for possible architectures and is widely used in medical AI. However, due to its black-box nature, explainability is ...
IEEE

A Large Language Model-Based Plagiarism Detection System Architecture for Academic Journals in Higher Education

Abstract: In recent years, academic misconduct in universities and research institutions has posed significant challenges to academic integrity and reputation. However, existing plagiarism detection ...