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Exploiting Deep Contrast Feature for Image Retrieval
Exploiting Deep Contrast Feature for Image Retrieval
In the field of content-based image retrieval (CBIR), fused feature-based methods have demonstrated their advanced perform...
Functional Connectivity Imbalance Between Positive and Negative Networks in Mild Cognitive Impairment via Feature Selection
Functional Connectivity Imbalance Between Positive and Negative Networks in Mild Cognitive Impairment via Feature Selection
Association A. 2019 Alzheimer’s disease facts and figures. Alzheimers Dement. 2019;15(3):321–87.Article  MATH  ...
Development of a Decision Support System for Performance Measurement of Social Movements
Development of a Decision Support System for Performance Measurement of Social Movements
Social movements encompass the collective actions of groups gathered under the same goal, operating within a specific orga...
An Asymmetric Semantic Segmentation Model via Lightweight Attention-Guided Feature Enhancement and Fusion
An Asymmetric Semantic Segmentation Model via Lightweight Attention-Guided Feature Enhancement and Fusion
Semantic segmentation is widely used in fields such as autonomous driving and unmanned aerial vehicle navigation. However,...
Dynamic Behavior of Three-Layer Fractional-Order Neural Networks with Multiple Delays
Dynamic Behavior of Three-Layer Fractional-Order Neural Networks with Multiple Delays
Most of the complex network in the real world are not single-layer networks, and networks will be connected with each othe...
A Novel Hyperparameter Optimization Approach for Supervised Classification: Phase Prediction of Multi-Principal Element Alloys
A Novel Hyperparameter Optimization Approach for Supervised Classification: Phase Prediction of Multi-Principal Element Alloys
In this paper, a hyperparameter optimization approach is proposed for the phase prediction of multi-principal element allo...
Learning to Calibrate Prototypes for Few-Shot Image Classification
Learning to Calibrate Prototypes for Few-Shot Image Classification
Few-shot learning (FSL) aims to generalise the model to novel classes by using a limited amount of discriminative samples ...
Attribute Reduction in a Hybrid Decision Information System Based on Fuzzy Conditional Information Entropy Using Iterative Model and Matrix Operation
Attribute Reduction in a Hybrid Decision Information System Based on Fuzzy Conditional Information Entropy Using Iterative Model and Matrix Operation
Attribute reduction of hybrid decision information systems (HDISs) is a significant research area within the field of mach...
Augmenting Cardiovascular Disease Prediction Through CWCF Integration Leveraging Harris Hawks Search in Deep Belief Networks
Augmenting Cardiovascular Disease Prediction Through CWCF Integration Leveraging Harris Hawks Search in Deep Belief Networks
Cardiovascular disease (CVD) is a major global health concern, demanding accurate predictive models to aid preventive heal...
Engaging Preference Optimization Alignment in Large Language Model for Continual Radiology Report Generation: A Hybrid Approach
Engaging Preference Optimization Alignment in Large Language Model for Continual Radiology Report Generation: A Hybrid Approach
Large language models (LLMs) remain relatively underutilized in medical imaging, particularly in radiology, which is essen...
HLAE: Hierarchical Local Attention Encoder for MRI Brain Tumor Image Classification
HLAE: Hierarchical Local Attention Encoder for MRI Brain Tumor Image Classification
MRI-based brain tumor classification is a challenging neuroimaging task, where the key lies in leveraging ensemble informa...
A Weakly Supervised Data Labeling Framework for Machine Lexical Normalization in Vietnamese Social Media
A Weakly Supervised Data Labeling Framework for Machine Lexical Normalization in Vietnamese Social Media
This study introduces an innovative automatic labeling framework to address the challenges of lexical normalization in soc...
Tweet Credibility Ranker: A Credibility Features’ Fusion Model
Tweet Credibility Ranker: A Credibility Features’ Fusion Model
Misinformation on social media has emerged as a modern weapon of warfare, disrupting societal peace, trust, justice, and d...
An Adaptive Neural Network Algorithm with Quasi Opposition-Based Learning for Numerical Optimization Problems
An Adaptive Neural Network Algorithm with Quasi Opposition-Based Learning for Numerical Optimization Problems
The structure of artificial neural networks and the biological nervous systems serve as the foundation for the creation of...
Application of Metaheuristic Algorithms with Supervised Machine Learning for Accurate Power Consumption Prediction
Application of Metaheuristic Algorithms with Supervised Machine Learning for Accurate Power Consumption Prediction
Accurate power consumption prediction is a crucial part of energy management. Some of the machine learning models that are...
Innovative Deep Learning Framework for Accurate Plant Disease Detection and Crop Productivity Enhancement
Innovative Deep Learning Framework for Accurate Plant Disease Detection and Crop Productivity Enhancement
In modern agriculture, the detection of plant diseases is crucial for enhancing crop productivity. Predicting disease onse...
Systematic Review and Thematic Analysis of Digital Games for Cognitive Enhancement in Children with Autism Spectrum Disorder: Toward a Conceptual Framework
Systematic Review and Thematic Analysis of Digital Games for Cognitive Enhancement in Children with Autism Spectrum Disorder: Toward a Conceptual Framework
Compared to typically developing people, children with autism spectrum disorder (ASD) have distinct cognitive and intellig...
Exploring Influence of Different Emotions on Decision-Making by Analyzing the Temporal, Spatial, and Spectral Domains of EEG
Exploring Influence of Different Emotions on Decision-Making by Analyzing the Temporal, Spatial, and Spectral Domains of EEG
Decision-making is a complex cognitive process, in which emotion is one of the most important factors. But insights into t...
Verifying Technical Indicator Effectiveness in Cryptocurrency Price Forecasting: a Deep-Learning Time Series Model Based on Sparrow Search Algorithm
Verifying Technical Indicator Effectiveness in Cryptocurrency Price Forecasting: a Deep-Learning Time Series Model Based on Sparrow Search Algorithm
Forecasting cryptocurrency prices is challenging due to market volatility and dynamic behavior. This study aims to enhance...
Global Exponential Synchronization of Clifford-Valued Memristive Fuzzy Neural Networks with Delayed Impulses
Global Exponential Synchronization of Clifford-Valued Memristive Fuzzy Neural Networks with Delayed Impulses
The global exponential synchronization of Clifford-valued memristive fuzzy neural networks (CLVMFNNs) with delayed impulse...
A Novel Heuristic Exploration Method Based on Action Effectiveness Constraints to Relieve Loop Enhancement Effect in Reinforcement Learning with Sparse Rewards
A Novel Heuristic Exploration Method Based on Action Effectiveness Constraints to Relieve Loop Enhancement Effect in Reinforcement Learning with Sparse Rewards
In realistic sparse reward tasks, existing theoretical methods cannot be effectively applied due to the low sampling proba...
Classification of Developmental and Brain Disorders via Graph Convolutional Aggregation
Classification of Developmental and Brain Disorders via Graph Convolutional Aggregation
While graph convolution-based methods have become the de-facto standard for graph representation learning, their applicati...
Non-linear Feature Selection Based on Convolution Neural Networks with Sparse Regularization
Non-linear Feature Selection Based on Convolution Neural Networks with Sparse Regularization
The efficacy of feature selection methods in dimensionality reduction and enhancing the performance of learning algorithms...
A Novel Regularized Extreme Learning Machine Based on $$L_{1}$$ -Norm and $$L_{2}$$ -Norm: a Sparsity Solution Alternative to Lasso and Elastic Net
A Novel Regularized Extreme Learning Machine Based on $$L_{1}$$ -Norm and $$L_{2}$$ -Norm: a Sparsity Solution Alternative to Lasso and Elastic Net
The aim of this study is to present a new regularized extreme learning machine (ELM) algorithm that can perform variable s...
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...
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