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The Antagonistic Alterations of Cerebellar Functional Segregation and Integration in Athletes with Fast Demands of Visual-Motor Coordination
The Antagonistic Alterations of Cerebellar Functional Segregation and Integration in Athletes with Fast Demands of Visual-Motor Coordination
The theoretical foundation of brain-computer interface partly lies in the neural mechanism of motor function plasticity. T...
Deep Learning Based Traffic Prediction Method for Digital Twin Network
Deep Learning Based Traffic Prediction Method for Digital Twin Network
Network traffic prediction (NTP) can predict future traffic leveraging historical data, which serves as proactive methods ...
Improving Coronary Heart Disease Prediction Through Machine Learning and an Innovative Data Augmentation Technique
Improving Coronary Heart Disease Prediction Through Machine Learning and an Innovative Data Augmentation Technique
Coronary heart disease (CHD) is a leading cause of death globally, with over 382,000 deaths in the USA alone in 2020. The ...
The Strange and Promising Relationship Between EEG and AI Methods of Analysis
The Strange and Promising Relationship Between EEG and AI Methods of Analysis
Nowadays, the utility of AI methods for classifying EEG data is widespread in research laboratories. The constant in this ...
Image Retrieval Using Object Semantic Aggregation Histogram
Image Retrieval Using Object Semantic Aggregation Histogram
Simulating primates’ ability to make fine visual discriminations for extracting visual features remains a challenge....
Constructing Three-Way Decision of Rough Fuzzy Sets from the Perspective of Uncertainties
Constructing Three-Way Decision of Rough Fuzzy Sets from the Perspective of Uncertainties
From the perspective of human cognition, three-way decision (3WD) explores thinking, problem solving, and information proc...
An Interpretable Neuro-symbolic Model for Raven’s Progressive Matrices Reasoning
An Interpretable Neuro-symbolic Model for Raven’s Progressive Matrices Reasoning
Raven’s Progressive Matrices (RPM) have been widely used as standard intelligence tests for human participants. Huma...
Few-Shot Object Detection with Weight Imprinting
Few-Shot Object Detection with Weight Imprinting
The goal of few-shot learning is to learn a solution to a problem from limited training samples. In recent years, with the...
A Hebbian Model to Account for Musical Expertise Differences in a Working Memory Task
A Hebbian Model to Account for Musical Expertise Differences in a Working Memory Task
The TBRS*C computational model provides a mathematical implementation of the cognitive processes involved in complex span ...
Vehicle Re-Identification by Separating Representative Spatial Features
Vehicle Re-Identification by Separating Representative Spatial Features
As a complex image classification problem, re-identification (ReID) requires the model to capture diverse representative f...
Haptic Recognition of Texture Surfaces Using Semi-Supervised Feature Learning Based on Sparse Representation
Haptic Recognition of Texture Surfaces Using Semi-Supervised Feature Learning Based on Sparse Representation
Haptic cognitive models are used to map the physical stimuli of texture surfaces to subjective haptic cognition, providing...
Deep Heuristic Evolutionary Regression Model Based on the Fusion of BiGRU and BiLSTM
Deep Heuristic Evolutionary Regression Model Based on the Fusion of BiGRU and BiLSTM
The input for stock market prediction is usually a period of stock price data with time series characteristics, which will...
Enhanced Quantum-Secure Ensemble Intrusion Detection Techniques for Cloud Based on Deep Learning
Enhanced Quantum-Secure Ensemble Intrusion Detection Techniques for Cloud Based on Deep Learning
The increasing popularity of cloud computing systems has drawn significant attention from academics and businesses for sev...
Cognitive Phenomenology Neuroscience and Computation
Cognitive Phenomenology Neuroscience and Computation
Phenomenology is concerned with the first-person experience of or about some object, and is generally related to sensory e...
Tensorized Anchor Graph Learning for Large-scale Multi-view Clustering
Tensorized Anchor Graph Learning for Large-scale Multi-view Clustering
With the continuous development of information acquisition technologies, large-scale multi-view data increases rapidly. Th...
Re-Thinking the Organization of Cortico-Basal Ganglia-Thalamo-Cortical Loops
Re-Thinking the Organization of Cortico-Basal Ganglia-Thalamo-Cortical Loops
First concepts of cortex-basal ganglia interactions suggested that cognitive functions are implemented through different p...
BrainNet with Connectivity Attention for Individualized Predictions Based on Multi-Facet Connections Extracted from Resting-State fMRI Data
BrainNet with Connectivity Attention for Individualized Predictions Based on Multi-Facet Connections Extracted from Resting-State fMRI Data
Resting-state functional magnetic resonance imaging (RS-fMRI) has great potential for clinical applications. This study ai...
Multi-Scale Convolutional Neural Network for Temporal Knowledge Graph Completion
Multi-Scale Convolutional Neural Network for Temporal Knowledge Graph Completion
Knowledge graph completion is a critical task in natural language processing. The task becomes more challenging on tempora...
A Novel Stock Index Direction Prediction Based on Dual Classifier Coupling and Investor Sentiment Analysis
A Novel Stock Index Direction Prediction Based on Dual Classifier Coupling and Investor Sentiment Analysis
Accurate prediction of stock trends is of great crucial to guiding investment management and financial policymaking. In re...
Prototype Theory Meets Word Embedding: A Novel Approach for Text Categorization via Granular Computing
Prototype Theory Meets Word Embedding: A Novel Approach for Text Categorization via Granular Computing
The problem of the information representation and interpretation coming from senses by the brain has plagued scientists fo...
Improvement of Facial Beauty Prediction Using Artificial Human Faces Generated by Generative Adversarial Network
Improvement of Facial Beauty Prediction Using Artificial Human Faces Generated by Generative Adversarial Network
Human beauty evaluation is a particularly difficult task. This task can be solved using deep learning methods. We propose ...
Integrating Economic Theory, Domain Knowledge, and Social Knowledge into Hybrid Sentiment Models for Predicting Crude Oil Markets
Integrating Economic Theory, Domain Knowledge, and Social Knowledge into Hybrid Sentiment Models for Predicting Crude Oil Markets
For several decades, sentiment analysis has been considered a key indicator for assessing market mood and predicting futur...
Learning-Based Stock Trending Prediction by Incorporating Technical Indicators and Social Media Sentiment
Learning-Based Stock Trending Prediction by Incorporating Technical Indicators and Social Media Sentiment
Stock trending prediction is a challenging task due to its dynamic and nonlinear characteristics. With the development of ...
A Grouping Cooperative Differential Evolution Algorithm for Solving Partially Separable Complex Optimization Problems
A Grouping Cooperative Differential Evolution Algorithm for Solving Partially Separable Complex Optimization Problems
Differential evolution (DE) is a widely accepted optimization algorithm inspired by the mechanisms of biological evolution...
Deep Intelligence: What AI Should Learn from Nature’s Imagination
Deep Intelligence: What AI Should Learn from Nature’s Imagination
Artificial intelligence (AI) has recently seen explosive growth and remarkable successes in several application areas. How...
Aspect-Based Sentiment Analysis of Customer Speech Data Using Deep Convolutional Neural Network and BiLSTM
Aspect-Based Sentiment Analysis of Customer Speech Data Using Deep Convolutional Neural Network and BiLSTM
The process of detecting sentiments of particular context from human speech emotions is naturally in-built for humans unli...
GLAN: GAN Assisted Lightweight Attention Network for Biomedical Imaging Based Diagnostics
GLAN: GAN Assisted Lightweight Attention Network for Biomedical Imaging Based Diagnostics
Manual assessment of biomedical imaging based diagnostics is limited as it is time-consuming and subjective. Bio-inspired ...
SRFFNet: Self-refine, Fusion and Feedback for Salient Object Detection
SRFFNet: Self-refine, Fusion and Feedback for Salient Object Detection
Many existing salient object detection models have achieved excellent results by fusing the progressive multi-layer featur...
Inductive Multi-View Semi-supervised Learning with a Consensus Graph
Inductive Multi-View Semi-supervised Learning with a Consensus Graph
Graphs have a crucial impact on the performance of any graph-based semi-supervised learning method, so their construction ...
Large-Kernel Attention for 3D Medical Image Segmentation
Large-Kernel Attention for 3D Medical Image Segmentation
Automated segmentation of multiple organs and tumors from 3D medical images such as magnetic resonance imaging (MRI) and c...
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