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Automatic Screening of COVID-19 Using an Optimized Generative Adversarial Network
Automatic Screening of COVID-19 Using an Optimized Generative Adversarial Network
The quick spread of coronavirus disease (COVID-19) has resulted in a global pandemic and more than fifteen million confirm...
Unmasking GAN-Generated Faces with Optimal Deep Learning and Cognitive Computing-Based Cutting-Edge Detection System
Unmasking GAN-Generated Faces with Optimal Deep Learning and Cognitive Computing-Based Cutting-Edge Detection System
The emergence of deep learning (DL) has improved the excellence of generated media. However, with the enlarged level of ph...
Pruning Deep Neural Networks for Green Energy-Efficient Models: A Survey
Pruning Deep Neural Networks for Green Energy-Efficient Models: A Survey
Over the past few years, larger and deeper neural network models, particularly convolutional neural networks (CNNs), have ...
Twin Bounded Support Vector Machine with Capped Pinball Loss
Twin Bounded Support Vector Machine with Capped Pinball Loss
In order to obtain a more robust and sparse classifier, in this paper, we propose a novel classifier termed as twin bounde...
Prescribed-Time Sampled-Data Control for the Bipartite Consensus of Linear Multi-Agent Systems in Singed Networks
Prescribed-Time Sampled-Data Control for the Bipartite Consensus of Linear Multi-Agent Systems in Singed Networks
This article examines the prescribed-time sampled-data control problem for multi-agent systems in signed networks. A time-...
Granular Syntax Processing with Multi-Task and Curriculum Learning
Granular Syntax Processing with Multi-Task and Curriculum Learning
Syntactic processing techniques are the foundation of natural language processing (NLP), supporting many downstream NLP ta...
Evaluative Item-Contrastive Explanations in Rankings
Evaluative Item-Contrastive Explanations in Rankings
The remarkable success of Artificial Intelligence in advancing automated decision-making is evident both in academia and i...
Disentangling User Cognitive Intent with Causal Reasoning for Knowledge-Enhanced Recommendation
Disentangling User Cognitive Intent with Causal Reasoning for Knowledge-Enhanced Recommendation
The primary objective of an effective recommender system is to provide accurate, varied, and personalized recommendations ...
Event-Triggered Adaptive Neural Control for Full State-Constrained Nonlinear Systems with Unknown Disturbances
Event-Triggered Adaptive Neural Control for Full State-Constrained Nonlinear Systems with Unknown Disturbances
This paper focuses on the adaptive control issue for a class of uncertain nonlinear systems subject to full state constrai...
Graph-Based Interactive Matching for Pairs of News Articles
Graph-Based Interactive Matching for Pairs of News Articles
Long-text document matching has been widely applied in many applications, such as topic detection and tracking and relativ...
An Enhanced Interactive and Multi-criteria Decision-Making (TODIM) Method with Probabilistic Dual Hesitant Fuzzy Sets for Risk Evaluation of Arctic Geopolitics
An Enhanced Interactive and Multi-criteria Decision-Making (TODIM) Method with Probabilistic Dual Hesitant Fuzzy Sets for Risk Evaluation of Arctic Geopolitics
The psychological factors of experts play a special role in the process of decision-making, especially in some situations ...
ArQuAD: An Expert-Annotated Arabic Machine Reading Comprehension Dataset
ArQuAD: An Expert-Annotated Arabic Machine Reading Comprehension Dataset
Machine Reading Comprehension (MRC) is a task that enables machines to mirror key cognitive processes involving reading, c...
Synchronization of Hypercomplex Neural Networks with Mixed Time-Varying Delays
Synchronization of Hypercomplex Neural Networks with Mixed Time-Varying Delays
This article discusses the fixed-time synchronization (FTS) of hypercomplex neural networks (HCNNs) with mixed time-varyin...
Motion Selectivity of the Local Filed Potentials in the Primary Visual Cortex of Rats: A Machine Learning Approach
Motion Selectivity of the Local Filed Potentials in the Primary Visual Cortex of Rats: A Machine Learning Approach
Using rodents as a model of physiological vision studies requires adequate information about their visual cortex. Although...
Shift-Equivariant Similarity-Preserving Hypervector Representations of Sequences
Shift-Equivariant Similarity-Preserving Hypervector Representations of Sequences
Hyperdimensional Computing (HDC), also known as Vector-Symbolic Architectures (VSA), is a promising framework for the deve...
Normal Template Mapping: An Association-Inspired Handwritten Character Recognition Model
Normal Template Mapping: An Association-Inspired Handwritten Character Recognition Model
In identifying objects, people usually associate memory templates to guide visual attention and determine the category of ...
A Mutual Information-Based Many-Objective Optimization Method for EEG Channel Selection in the Epileptic Seizure Prediction Task
A Mutual Information-Based Many-Objective Optimization Method for EEG Channel Selection in the Epileptic Seizure Prediction Task
Epileptic seizure prediction using multi-channel electroencephalogram (EEG) signals is very important in clinical therapy....
Diabetic Foot Ulcer Detection: Combining Deep Learning Models for Improved Localization
Diabetic Foot Ulcer Detection: Combining Deep Learning Models for Improved Localization
Diabetes mellitus (DM) can cause chronic foot issues and severe infections, including Diabetic Foot Ulcers (DFUs) that hea...
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...
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...
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