Adaptive frequency band attention-guided CNN–BiLSTM for Spatial–Spectral–Temporal EEG emotion recognition
The framework, developed by Rabita Hasan and Sheikh Md.
Tag: BiLSTM
Simple Machine Learning Outperforms Deep Models in Somali Dialect Test
A new study reports that a simple Naive Bayes classifier reached 99.05 percent accuracy in distinguishing Somali's MAXAA TIRI and ...
Temporal deep learning model predicts aging of power composite insulators
Researchers report a hybrid BiLSTM framework with wavelet feature extraction and modified Archimedes optimization that classifies composite insulator aging states ...
Six AI models read thousands of cancer narratives and mostly disagree on what they feel
A multi-model NLP study of more than 200 online cancer narrative sources found negative sentiment dominated diagnosis and treatment discourse, ...
AI Reads Faces and Voices to Spot Depression with Directional Causal Fusion
Researchers report a Mamba-BiLSTM framework with Granger-inspired directional causal fusion that reached 81.86 percent accuracy for multimodal depression detection on ...
AI System Turns Hotel Guest Reviews into Automated Management Decisions
A new study combines whole-word-masked BERT, a bidirectional LSTM and deep reinforcement learning to turn Chinese hotel guest reviews directly ...
Deep Reinforcement Learning Tracks Drag While Attention-Based BiLSTM Speeds Projectile Trajectory Prediction
A new study combines TD3 reinforcement learning for drag coefficient identification with an attention-based BiLSTM that cuts trajectory prediction error ...
Deep learning system scores long jump technique and lifts student performance
Researchers combined YOLOv5, DeepSORT, OpenPose, BiLSTM and Dynamic Time Warping into a long jump teaching system that scored take-off movements ...
Hybrid model detects suicidal ideation in Spanish social media posts
A hybrid BERT, BiLSTM and BiTCN model classified suicidal ideation in Spanish social media posts with F1-scores of 93.51% and ...
AI Models Detect Suicidal Ideation in Amharic Social Media Posts
An ensemble of machine learning models detected suicidal ideation in Amharic social media posts with up to 83.3 percent accuracy, ...
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Mothers who receive childcare support from maternal grandparents show more parental warmth, finds NTU Singapore study
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University of Seville Breaks 120-Year-Old Mystery, Revises a Key Einstein Concept
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Bee body mass, pathogens and local climate influence heat tolerance
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Researchers record first-ever images and data of a shark experiencing a boat strike
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Groundbreaking Clinical Trial Reveals Lubiprostone Enhances Kidney Function
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