IEEE

WavTSK: An Interpretable Fuzzy Network With Learnable Wavelet-Based Feature Extraction for Motor Imagery EEG Decoding

Abstract: Decoding motor imagery (MI) from electroencephalogram (EEG) signals is a cornerstone of brain–computer interface (BCI) systems. However, existing methods often face a critical tradeoff ...
IEEE

A Hybrid Feature Extraction and Classification Framework for Depression Detection using Deep Learning and Machine Learning Techniques

Abstract: Depression is most common mental disorder that is affecting approximately 280 million individuals in the world. The stigma and lack of acceptance and awareness is still influencing people ...
GitHub

CausalInferenceLab/awesome-causal-inference-python

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IEEE

Intelligent Fault Diagnosis of Motor Bearings Based on Dual-Branch Depthwise Separable CNN With Acoustic–Vibration Signal Fusion

Abstract: The intelligent diagnosis of motor bearings under complex working conditions presents significant challenges, including insufficient feature extraction, limited reliability of ...
IEEE

SCAFNet: A Semantic Compensated Adaptive Fusion Network for Remote Sensing Images Change Detection

Abstract: Current CNN-Transformer hybrid methods for remote sensing change detection aim to address the limitations of CNNs’ constrained receptive fields and Transformers’ local detail insensitivity.
IEEE

Multilayer Feature Extraction Object Detection Based on Deep Forest

Abstract: With the emergence of various large-scale deep-learning models, in remote sensing images, the object detection effect is also plagued by complex calculations, high costs, and high ...
IEEE

Gender estimation based on supervised HOG, Action Units and unsupervised CNN feature extraction

Abstract: In this paper, a deep-learning based architecture is proposed to estimate gender which includes both supervised and unsupervised facial feature extraction techniques and a deep network to ...
GitHub

Lelalomos/financial_research_01

A PyTorch-based CRNN (CNN + BiLSTM + Attention) model for predicting stock price movements. The model learns patterns from S&P 500 stocks using technical indicators, candlestick patterns, and external ...
IEEE

UAGLNet: Uncertainty-Aggregated Global-Local Fusion Network with Cooperative CNN-Transformer for Building Extraction

Abstract: Building extraction from remote sensing images is a challenging task due to the complex structure variations of the buildings. Existing methods employ convolutional or self-attention blocks ...
IEEE

Advanced Epilepsy Severity Analysis and Diagnosis via EEG Signal Classification Using Modified LeNet-CNN

Abstract: There are just two stages of sensitivity that the dual rating system can detect, which is its biggest drawback. By modifying the LeNET-CNN framework and including the EMD transform, a ...
IEEE

Single-Channel Time-Frequency Overlapping Signal Modulation Recognition Network Based on Multi-Domain Adaptive Feature Fusion

Abstract: With the application of massive wireless devices, the receiver often receives mixed signals with time-frequency overlapping. Automatic modulation classification (AMC) of such mixed signals ...