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MC-GAT: Multi-Channel Graph Attention Networks for Capturing Diverse Information in Complex Graphs
MC-GAT: Multi-Channel Graph Attention Networks for Capturing Diverse Information in Complex Graphs
Graph attention networks (GAT), which have strong performance in tackling various analytical tasks on network data, have a...
Gradient-Based Competitive Learning: Theory
Gradient-Based Competitive Learning: Theory
Deep learning has been recently used to extract the relevant features for representing input data also in the unsupervised...
Optimizing Sentiment Analysis: A Cognitive Approach with Negation Handling via Mathematical Modelling
Optimizing Sentiment Analysis: A Cognitive Approach with Negation Handling via Mathematical Modelling
Negation handling is a crucial aspect of sentiment analysis, as it presents challenges to accurate sentiment classificatio...
A Novel Convolutional Neural Network for Head Detection and Pose Estimation in Complex Environments from Single-Depth Images
A Novel Convolutional Neural Network for Head Detection and Pose Estimation in Complex Environments from Single-Depth Images
Computer vision based on neural networks is an important part of modern cognitive research. As important applications, hea...
Fast Clustering for Cooperative Perception Based on LiDAR Adaptive Dynamic Grid Encoding
Fast Clustering for Cooperative Perception Based on LiDAR Adaptive Dynamic Grid Encoding
This study introduces a strategy inspired by cooperative behavior in nature to enhance information sharing among autonomou...
A Novel Feature Fusion Approach for Classification of Motor Imagery EEG Based on Hierarchical Extreme Learning Machine
A Novel Feature Fusion Approach for Classification of Motor Imagery EEG Based on Hierarchical Extreme Learning Machine
Because feature extraction from electroencephalogram (EEG) signals is essential for cognitive investigations, effective fe...
Trustworthy Artificial Intelligence Based on an Explicable Temporal Feature Network for Industrial Fault Diagnosis
Trustworthy Artificial Intelligence Based on an Explicable Temporal Feature Network for Industrial Fault Diagnosis
Artificial intelligence is extensively utilized across various high-risk domains, and ensuring the safety, reliability, an...
Machine Un-learning: An Overview of Techniques, Applications, and Future Directions
Machine Un-learning: An Overview of Techniques, Applications, and Future Directions
ML applications proliferate across various sectors. Large internet firms employ ML to train intelligent models using vast ...
SPS Vision Net: Measuring Sensory Processing Sensitivity via an Artificial Neural Network
SPS Vision Net: Measuring Sensory Processing Sensitivity via an Artificial Neural Network
Sensory processing sensitivity (SPS) is a biological trait associated with heightened sensitivity and responsivity to the ...
A Multi-attention Triple Decoder Deep Convolution Network for Breast Cancer Segmentation Using Ultrasound Images
A Multi-attention Triple Decoder Deep Convolution Network for Breast Cancer Segmentation Using Ultrasound Images
Breast cancer (BC) is a widely diagnosed deadly disease commonly present in middle-aged women around the globe. Ultrasound...
Explainable Artificial Intelligence in Alzheimer’s Disease Classification: A Systematic Review
Explainable Artificial Intelligence in Alzheimer’s Disease Classification: A Systematic Review
The unprecedented growth of computational capabilities in recent years has allowed Artificial Intelligence (AI) m...
Multispectral Image Quality Improvement Based on Global Iterative Fusion Constrained by Meteorological Factors
Multispectral Image Quality Improvement Based on Global Iterative Fusion Constrained by Meteorological Factors
It has been proven that the refractive index is related to meteorological parameters in physics. The temperature changes t...
Cognitively-Inspired Multi-Scale Spectral-Spatial Transformer for Hyperspectral Image Super-Resolution
Cognitively-Inspired Multi-Scale Spectral-Spatial Transformer for Hyperspectral Image Super-Resolution
The hyperspectral image (HSI) super-resolution (SR) without auxiliary high-resolution images is a challenging task in comp...
Stability Analysis of Quaternion-Valued Neutral Neural Networks with Generalized Activation Functions
Stability Analysis of Quaternion-Valued Neutral Neural Networks with Generalized Activation Functions
Stability is a central issue in the study of dynamical systems, and quaternion-valued neural networks (QVNNs) perform well...
State-of-the-Art of Stress Prediction from Heart Rate Variability Using Artificial Intelligence
State-of-the-Art of Stress Prediction from Heart Rate Variability Using Artificial Intelligence
Recent advancements in the manufacturing and commercialisation of miniaturised sensors and low-...
Attention-Guided Multi-Scale Fusion Network for Similar Objects Semantic Segmentation
Attention-Guided Multi-Scale Fusion Network for Similar Objects Semantic Segmentation
Image segmentation accuracy is critical in marine ecological detection utilizing unmanned aerial vehicles (UAVs). By flyin...
Improving Knowledge Learning Through Modelling Students’ Practice-Based Cognitive Processes
Improving Knowledge Learning Through Modelling Students’ Practice-Based Cognitive Processes
Practice is an essential means by which humans and animals engage in cognitive activities. Intelligent tutoring systems, w...
CoDeS: A Deep Learning Framework for Identifying COVID-Caused Depression Symptoms
CoDeS: A Deep Learning Framework for Identifying COVID-Caused Depression Symptoms
Depression is a serious mental health condition that affects a person’s ability to feel happy and engaged in activit...
Construction of a Hierarchical Organization in Semantic Memory: A Model Based on Neural Masses and Gamma-Band Synchronization
Construction of a Hierarchical Organization in Semantic Memory: A Model Based on Neural Masses and Gamma-Band Synchronization
Semantic memory is characterized by a hierarchical organization of concepts based on shared properties. However, this aspe...
Hardware-Optimized Reservoir Computing System for Edge Intelligence Applications
Hardware-Optimized Reservoir Computing System for Edge Intelligence Applications
Edge artificial intelligence or edge intelligence is an ever-growing research area due to the current popularization of th...
Limitations of the Recall Capabilities in Delay-Based Reservoir Computing Systems
Limitations of the Recall Capabilities in Delay-Based Reservoir Computing Systems
We analyse the memory capacity of a delay-based reservoir computer with a Hopf normal form as nonlinearity and numerically...
Personality Enhanced Emotion Generation Modeling for Dialogue Systems
Personality Enhanced Emotion Generation Modeling for Dialogue Systems
Emotion plays a crucial role in human communication, as it adds depth and richness to conversations. In recent years, ther...
Online Signature Recognition: A Biologically Inspired Feature Vector Splitting Approach
Online Signature Recognition: A Biologically Inspired Feature Vector Splitting Approach
This research introduces an innovative approach to explore the cognitive and biologically inspired underpinnings of featur...
Two-Stage Deep Ensemble Paradigm Based on Optimal Multi-scale Decomposition and Multi-factor Analysis for Stock Price Prediction
Two-Stage Deep Ensemble Paradigm Based on Optimal Multi-scale Decomposition and Multi-factor Analysis for Stock Price Prediction
Stock price forecasting is important for financial risk management and investment decisions. However, traditional forecast...
Bifurcation−Driven Tipping in A Novel Bicyclic Crossed Neural Network with Multiple Time Delays
Bifurcation−Driven Tipping in A Novel Bicyclic Crossed Neural Network with Multiple Time Delays
Anatomical experiments have proved that a large number of ring structures exist in neural networks. Therefore, many schola...
Neurosymbolic AI for Mining Public Opinions about Wildfires
Neurosymbolic AI for Mining Public Opinions about Wildfires
Wildfires are among the most threatening hazards to life, property, well-being, and the environment. Studying public opini...
TEGAN: Transformer Embedded Generative Adversarial Network for Underwater Image Enhancement
TEGAN: Transformer Embedded Generative Adversarial Network for Underwater Image Enhancement
Underwater robots are widely used in underwater missions. However, due to complex scenes, it is difficult to obtain high-q...
Assessing the Potential of Data Augmentation in EEG Functional Connectivity for Early Detection of Alzheimer’s Disease
Assessing the Potential of Data Augmentation in EEG Functional Connectivity for Early Detection of Alzheimer’s Disease
Electroencephalographic (EEG) signals are acquired non-invasively from electrodes placed on the scalp. Experts in the fiel...
Prototype Consistency Learning for Medical Image Segmentation by Cross Pseudo Supervision
Prototype Consistency Learning for Medical Image Segmentation by Cross Pseudo Supervision
Due to the acquisition of anatomical/pathological labels is expensive and time-consuming, semi-supervised semantic segment...
A Novel Ensemble-Learning-Based Convolution Neural Network for Handling Imbalanced Data
A Novel Ensemble-Learning-Based Convolution Neural Network for Handling Imbalanced Data
Deep-learning-based fault diagnosis of wind turbine has played a significant role in advancing the renewable energy indust...
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