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Learning from Failure: Towards Developing a Disease Diagnosis Assistant That Also Learns from Unsuccessful Diagnoses
Learning from Failure: Towards Developing a Disease Diagnosis Assistant That Also Learns from Unsuccessful Diagnoses
In recent years, automatic disease diagnosis has gained immense popularity in research and industry communities. Humans le...
Cognitive Intelligent Decisions for Big Data and Cloud Computing in Industrial Applications using Trifold Algorithms
Cognitive Intelligent Decisions for Big Data and Cloud Computing in Industrial Applications using Trifold Algorithms
In contemporary real-time applications, diminutive devices are increasingly employing a greater portion of the spectrum to...
Multi-Modal Generative DeepFake Detection via Visual-Language Pretraining with Gate Fusion for Cognitive Computation
Multi-Modal Generative DeepFake Detection via Visual-Language Pretraining with Gate Fusion for Cognitive Computation
With the widespread adoption of deep learning, there has been a notable increase in the prevalence of multimodal deepfake ...
Towards Long-Term Remembering in Federated Continual Learning
Towards Long-Term Remembering in Federated Continual Learning
Federated Continual Learning (FCL) involves learning from distributed data on edge devices with incremental knowledge. How...
SPEI-FL: Serverless Privacy Edge Intelligence-Enabled Federated Learning in Smart Healthcare Systems
SPEI-FL: Serverless Privacy Edge Intelligence-Enabled Federated Learning in Smart Healthcare Systems
Smart healthcare systems promise significant benefits for fast and accurate medical decisions. However, working with perso...
Advancing Medical Imaging Through Generative Adversarial Networks: A Comprehensive Review and Future Prospects
Advancing Medical Imaging Through Generative Adversarial Networks: A Comprehensive Review and Future Prospects
In medical imaging, traditional methods have long been relied upon. However, the integration of Generative Adversarial Net...
Explainable Histopathology Image Classification with Self-organizing Maps: A Granular Computing Perspective
Explainable Histopathology Image Classification with Self-organizing Maps: A Granular Computing Perspective
The automatic analysis of histology images is an open research field where machine learning techniques and neural networks...
Cognitive Tracing Data Trails: Auditing Data Provenance in Discriminative Language Models Using Accumulated Discrepancy Score
Cognitive Tracing Data Trails: Auditing Data Provenance in Discriminative Language Models Using Accumulated Discrepancy Score
The burgeoning practice of unauthorized acquisition and utilization of personal textual data (e.g., social media comments ...
CPD-NSL: A Two-Stage Brain Effective Connectivity Network Construction Method Based on Dynamic Bayesian Network
CPD-NSL: A Two-Stage Brain Effective Connectivity Network Construction Method Based on Dynamic Bayesian Network
Current brain science reveals that the connectivity patterns of the human brain are constantly changing when performing di...
Generative AI and Cognitive Computing-Driven Intrusion Detection System in Industrial CPS
Generative AI and Cognitive Computing-Driven Intrusion Detection System in Industrial CPS
Industrial Cyber-Physical Systems (ICPSs) are becoming more and more networked and essential to modern infrastructure. Thi...
A Novel Memristors Based Echo State Network Model Inspired by the Brain’s Uni-hemispheric Slow-Wave Sleep Characteristics
A Novel Memristors Based Echo State Network Model Inspired by the Brain’s Uni-hemispheric Slow-Wave Sleep Characteristics
Memristors serve as electronic components with the ability to store charge and demonstrate resistive states, which are sim...
Optimization Based Deep Learning for COVID-19 Detection Using Respiratory Sound Signals
Optimization Based Deep Learning for COVID-19 Detection Using Respiratory Sound Signals
The COVID-19 prediction process is more indispensable to handle the spread and death occurred rate because of COVID-19. Ho...
A Review of Key Technologies for Emotion Analysis Using Multimodal Information
A Review of Key Technologies for Emotion Analysis Using Multimodal Information
Emotion analysis, an integral aspect of human–machine interactions, has witnessed significant advancements in recent...
Enhanced Android Ransomware Detection Through Hybrid Simultaneous Swarm-Based Optimization
Enhanced Android Ransomware Detection Through Hybrid Simultaneous Swarm-Based Optimization
Ransomware is a significant security threat that poses a serious risk to the security of smartphones, and its impact on po...
RA-Net: Region-Aware Attention Network for Skin Lesion Segmentation
RA-Net: Region-Aware Attention Network for Skin Lesion Segmentation
The precise segmentation of skin lesion in dermoscopic images is essential for the early detection of skin cancer. However...
Counterfactual Explanations in the Big Picture: An Approach for Process Prediction-Driven Job-Shop Scheduling Optimization
Counterfactual Explanations in the Big Picture: An Approach for Process Prediction-Driven Job-Shop Scheduling Optimization
In this study, we propose a pioneering framework for generating multi-objective counterfactual explanations in job-shop sc...
Detection of Cardiovascular Diseases Using Data Mining Approaches: Application of an Ensemble-Based Model
Detection of Cardiovascular Diseases Using Data Mining Approaches: Application of an Ensemble-Based Model
Cardiovascular diseases are the leading contributor of mortality worldwide. Accurate cardiovascular dise...
Smart Data Driven Decision Trees Ensemble Methodology for Imbalanced Big Data
Smart Data Driven Decision Trees Ensemble Methodology for Imbalanced Big Data
Differences in data size per class, also known as imbalanced data distribution, have become a common problem affecting dat...
Efficient Deep Learning Approach for Diagnosis of Attention-Deficit/Hyperactivity Disorder in Children Based on EEG Signals
Efficient Deep Learning Approach for Diagnosis of Attention-Deficit/Hyperactivity Disorder in Children Based on EEG Signals
Attention-deficit/hyperactivity disorder (ADHD) is a behavioral disorder in children that can persist into adulthood if no...
Evaluating Explainable Machine Learning Models for Clinicians
Evaluating Explainable Machine Learning Models for Clinicians
Gaining clinicians’ trust will unleash the full potential of artificial intelligence (AI) in medicine, and explainin...
Vision-Enabled Large Language and Deep Learning Models for Image-Based Emotion Recognition
Vision-Enabled Large Language and Deep Learning Models for Image-Based Emotion Recognition
The significant advancements in the capabilities, reasoning, and efficiency of artificial intelligence (AI)-based tools an...
Generative Adversarial Network-Assisted Framework for Power Management
Generative Adversarial Network-Assisted Framework for Power Management
The rise in power consumption (PC) is caused by several factors such as the growing global population, urbanization, techn...
Quasi-projective Synchronization Control of Delayed Stochastic Quaternion-Valued Fuzzy Cellular Neural Networks with Mismatched Parameters
Quasi-projective Synchronization Control of Delayed Stochastic Quaternion-Valued Fuzzy Cellular Neural Networks with Mismatched Parameters
This paper deals with the quasi-projective synchronization problem of delayed stochastic quaternion fuzzy cellular neural ...
Investigating the Influence of Scene Video on EEG-Based Evaluation of Interior Sound in Passenger Cars
Investigating the Influence of Scene Video on EEG-Based Evaluation of Interior Sound in Passenger Cars
The evaluation of automobile sound quality is an important research topic in the interior sound design of passenger car, a...
Multi-resolution Twinned Residual Auto-Encoders (MR-TRAE)—A Novel DL Model for Image Multi-resolution
Multi-resolution Twinned Residual Auto-Encoders (MR-TRAE)—A Novel DL Model for Image Multi-resolution
In this paper, we design and evaluate the performance of the Multi-resolution Twinned Residual Auto-Encoders (MR-TRAE) mod...
Generative Model-Driven Synthetic Training Image Generation: An Approach to Cognition in Railway Defect Detection
Generative Model-Driven Synthetic Training Image Generation: An Approach to Cognition in Railway Defect Detection
Recent advancements in cognitive computing, through the integration of artificial intelligence (AI) techniques, have facil...
Pairwise-Pixel Self-Supervised and Superpixel-Guided Prototype Contrastive Loss for Weakly Supervised Semantic Segmentation
Pairwise-Pixel Self-Supervised and Superpixel-Guided Prototype Contrastive Loss for Weakly Supervised Semantic Segmentation
Semantic segmentation plays an important role in many fields because of its powerful ability to classify each pixel effici...
NeuralPMG: A Neural Polyphonic Music Generation System Based on Machine Learning Algorithms
NeuralPMG: A Neural Polyphonic Music Generation System Based on Machine Learning Algorithms
The realm of music composition, augmented by technological advancements such as computers and related equipment, has under...