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Artificial Intelligence for Neuroscience and Emotional Systems : 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024, Olhâo, Portugal, June 4-7, 2024, Proceedings, Part I
Artificial Intelligence for Neuroscience and Emotional Systems : 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024, Olhâo, Portugal, June 4-7, 2024, Proceedings, Part I
Autore Ferrández Vicente José Manuel
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer, , 2024
Descrizione fisica 1 online resource (560 pages)
Altri autori (Persone) Val CalvoMikel
AdeliHojjat
Collana Lecture Notes in Computer Science Series
ISBN 3-031-61140-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Machine Learning in Neuroscience -- Morning Anxiety Detection Through Smartphone-Based Photoplethysmography Signals Analysis Using Machine Learning Methods -- 1 Introduction -- 2 Methods -- 2.1 Data Collection -- 2.2 Pulse Wave Extraction -- 2.3 Feature Extraction -- 2.4 Stress Classification -- 2.5 Fisher's Discriminant Ratio -- 3 Results and Discussion -- 4 Conclusion -- References -- Visualizing Brain Synchronization: An Explainable Representation of Phase-Amplitude Coupling -- 1 Introduction -- 2 Materials and Methods -- 2.1 The LEEDUCA Dataset -- 2.2 Data Preprocessing -- 2.3 Phase-Amplitude Coupling -- 2.4 Visualization of Local PAC Patterns -- 3 Consistency of Temporal Patterns -- 4 Results and Discussion -- 5 Conclusions -- References -- Enhancing Neuronal Coupling Estimation by NIRS/EEG Integration -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset and Preprocessing -- 2.2 CFS Image Sequences -- 2.3 fNIRS Functional Activation -- 2.4 Classification -- 3 Results -- 4 Conclusions and Future Work -- References -- Causal Mechanisms of Dyslexia via Connectogram Modeling of Phase Synchrony -- 1 Introduction -- 2 Material and Methods -- 2.1 Data Acquisition -- 2.2 Preprocessing -- 2.3 Hilbert Transform -- 2.4 Granger Causality -- 2.5 Feature Selection -- 2.6 Connectograms -- 2.7 Machine Learning Classification -- 3 Results -- 4 Conclusions -- References -- Explainable Exploration of the Interplay Between HRV Features and EEG Local Connectivity Patterns in Dyslexia -- 1 Introduction -- 2 Materials and Methods -- 2.1 Database -- 2.2 Cross Frequency Coupling with ISPC -- 2.3 Heart Rate Variability Descriptors -- 2.4 Explainable Regression Experiments -- 3 Results -- 4 Discussion -- 5 Conclusion -- References.
Enhancing Intensity Differences in EEG Cross-Frequency Coupling Maps for Dyslexia Detection -- 1 Introduction -- 2 Materials and Methods -- 2.1 Database -- 2.2 Generation of CFC Maps from EEG Signals -- 2.3 Enhancing Differences in CFS Maps Through Histogram Transformation -- 2.4 Quantification of the Improvement -- 3 Results -- 4 Discussion and Conclusions -- References -- Improving Prediction of Mortality in ICU via Fusion of SelectKBest with SMOTE Method and Extra Tree Classifier -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 3.1 Dataset Used -- 3.2 Preprocessing -- 3.3 AutoML -- 4 Result and Discussion -- 5 Conclusion -- References -- A Cross-Modality Latent Representation for the Prediction of Clinical Symptomatology in Parkinson's Disease -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset and Preprocessing -- 2.2 Multi-modal Joint Latent Variable Model -- 2.3 Evaluation -- 3 Results and Discussion -- 4 Conclusions -- References -- Zero-Shot Ensemble of Language Models for Fine-Grain Mental-Health Topic Classification -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 4 Experiments and Results -- 5 Conclusions -- References -- Enhancing Interpretability in Machine Learning: A Focus on Genetic Network Programming, Its Variants, and Applications -- 1 Introduction -- 2 The Most Important Versions of GNP -- 2.1 Some Specific Applications of GNP Algorithm -- 3 Conclusion and Future Works -- References -- Enhancing Coronary Artery Disease Classification Using Optimized MLP Based on Genetic Algorithm -- 1 Introduction -- 2 Related Works -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 Data Preprocessing -- 3.3 The Important Process of This Study -- 4 Results and Discussion -- 5 Conclusion -- References -- Extracting Heart Rate Variability from NIRS Signals for an Explainable Detection of Learning Disorders.
1 Introduction -- 2 Material and Methods -- 2.1 Participants -- 2.2 NIRS Acquisition -- 2.3 Extraction of Heart Signal from NIRS -- 2.4 Preprocessing -- 2.5 Classification and Explainability -- 3 Results -- 4 Conclusions and Future Work -- References -- Diagnosis of Parkinson Disease from EEG Signals Using a CNN-LSTM Model and Explainable AI -- 1 Introduction -- 2 Proposed Method -- 2.1 Dataset -- 2.2 Preprocessing -- 2.3 Deep Learning Model -- 3 Statistical Metrics -- 4 Experiment Results -- 5 Discussion, Conclusion, and Future Works -- References -- Early Diagnosis of Schizophrenia in EEG Signals Using One Dimensional Transformer Model -- 1 Introduction -- 2 Proposed Method -- 2.1 Dataset -- 2.2 Preprocessing -- 2.3 Feature Extraction Based on Transformer -- 2.4 Classification -- 3 Statistical Metrics -- 4 Experiment Results -- 5 Discussion, Conclusion, and Future Works -- References -- Diagnosis of Schizophrenia in EEG Signals Using dDTF Effective Connectivity and New PreTrained CNN and Transformer Models -- 1 Introduction -- 2 Proposed Method -- 2.1 Dataset -- 2.2 Preprocessing -- 2.3 Feature Extraction and Classification -- 3 Experiment Results -- 4 Discussion, Conclusion, and Future Works -- References -- A Survey on EEG Phase Amplitude Coupling to Speech Rhythm for the Prediction of Dyslexia -- 1 Introduction -- 2 Methods -- 2.1 Data Acquisition and Preprocessing -- 2.2 Cross-Frequency Coupling -- 2.3 Feature Aggregation and Classification -- 2.4 Evaluation and Interpretability -- 3 Results and Discussion -- 3.1 Best Performing Stimuli and PAC Measures -- 3.2 Effect of Classification Hyperparameters -- 3.3 Assymetric Differences Between DLX and CTL -- 4 Conclusions -- References -- Comprehensive Evaluation of Stroke Rehabilitation Dynamics: Integrating Brain-Computer Interface with Robotized Orthesic Hand and Longitudinal EEG Changes.
1 Introduction -- 2 Material and Methods -- 2.1 Participants -- 2.2 Description of the Experimentation -- 2.3 EEG Data Analysis -- 3 Results -- 3.1 Time Frequency -- 3.2 Topographic Maps -- 3.3 Power Bands -- 4 Discussion, Study Limitations and Future Work -- 5 Conclusion -- References -- PDBIGDATA: A New Database for Parkinsonism Research Focused on Large Models -- 1 Introduction -- 2 Database Description -- 3 Experiments and Results -- 4 Conclusions -- References -- A Comparative Study of Deep Learning Approaches for Cognitive Impairment Diagnosis Based on the Clock-Drawing Test -- 1 Introduction -- 2 Materials and Methods -- 2.1 CDT Databases -- 2.2 Image Preprocessing -- 2.3 Convolutional Neural Network -- 2.4 Attentive Pairwise Interaction Network -- 3 Experiments and Results -- 4 Discussion -- 5 Conclusion -- References -- Artificial Intelligence in Neurophysiology -- Prediction of Burst Suppression Occurrence Under General Anaesthesia Using Pre-operative EEG Signals -- 1 Introduction -- 2 Methods -- 2.1 Data -- 2.2 Pre-processing -- 2.3 Training -- 2.4 Models Evaluation -- 2.5 Generating Explanations with SHAP -- 3 Experiments -- 4 Results and Discussion -- 4.1 Models Evaluation -- 4.2 Explainability Analysis -- 4.3 Limitations and Future Work -- 5 Conclusion -- References -- Advances in Denoising Spikes Waveforms for Electrophysiological Recordings -- 1 Introduction -- 2 Methods -- 2.1 Acquisition System and Dataset -- 2.2 Neural Signal Denoising -- 2.3 Spike Sorting -- 2.4 Implementation Details -- 2.5 Software Testing -- 3 Results -- 3.1 Denoising and Spike Extraction Quality Measurement -- 4 Discussion -- 5 Conclusions -- References -- Analysis of Anxiety Caused by Fasting in Obesity Patients Using EEG Signals -- 1 Introduction -- 2 Materials and Methods -- 2.1 Subjects -- 2.2 Procedure -- 2.3 Data Processing -- 3 Results and Discussion.
4 Conclusions -- References -- Evolution of EEG Fractal Dimension Along a Sequential Finger Movement Task -- 1 Introduction: Fractal Dimension and its Application on EEG Signals Analysis -- 2 Materials and Methods -- 2.1 Dataset and Motor Task -- 2.2 EEG Signals Preprocessing -- 2.3 EMG Signals Preprocessing -- 2.4 Katz Fractal Dimension -- 2.5 KFD Time Windows -- 3 Results -- 4 Conclusion -- References -- Neuromotor and Cognitive Disorders -- Stress Classification Model Using Speech: An Ambulatory Protocol-Based Database Study -- 1 Introduction -- 2 Methods -- 2.1 Database -- 2.2 Feature Extraction -- 2.3 Supervised Classification -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Exploring Spatial Cognition: Comparative Analysis of Agent-Based Models in Dynamic and Static Environments -- 1 Introduction -- 2 Methodology -- 2.1 EvoJAX -- 2.2 Materials and Method -- 2.3 Results -- 3 Conclusions and Future Directions -- References -- Machine Learning for Personality Type Classification on Textual Data -- 1 Introduction -- 2 Background -- 3 Materials and Methods -- 3.1 Data Collection: -- 3.2 Feature Extraction -- 3.3 Target Classes -- 3.4 Classification Models -- 3.5 Performance Evaluation Metrics -- 4 Results -- 5 Conclusions -- References -- Grad-CAM Applied to the Detection of Instruments Used in Facial Presentation Attacks -- 1 Introduction -- 2 Related Work and Background -- 2.1 PAD Techniques -- 2.2 XAI Techniques -- 3 Methods and Materials -- 3.1 Design and Implementation -- 3.2 eXpainable Artificial Intelligence Grad-CAM -- 3.3 Procediment -- 3.4 Statistical Analysis -- 3.5 Database -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- Comparison of an Accelerated Garble Embedding Methodology for Privacy Preserving in Biomedical Data Analytics -- 1 Introduction -- 1.1 State of the Art -- 2 Theoretical Framework.
2.1 Information Comparison.
Record Nr. UNISA-996601560703316
Ferrández Vicente José Manuel  
Cham : , : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Artificial Intelligence for Neuroscience and Emotional Systems : 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024, Olhâo, Portugal, June 4-7, 2024, Proceedings, Part I
Artificial Intelligence for Neuroscience and Emotional Systems : 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024, Olhâo, Portugal, June 4-7, 2024, Proceedings, Part I
Autore Ferrández Vicente José Manuel
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer, , 2024
Descrizione fisica 1 online resource (560 pages)
Altri autori (Persone) Val CalvoMikel
AdeliHojjat
Collana Lecture Notes in Computer Science Series
ISBN 3-031-61140-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Machine Learning in Neuroscience -- Morning Anxiety Detection Through Smartphone-Based Photoplethysmography Signals Analysis Using Machine Learning Methods -- 1 Introduction -- 2 Methods -- 2.1 Data Collection -- 2.2 Pulse Wave Extraction -- 2.3 Feature Extraction -- 2.4 Stress Classification -- 2.5 Fisher's Discriminant Ratio -- 3 Results and Discussion -- 4 Conclusion -- References -- Visualizing Brain Synchronization: An Explainable Representation of Phase-Amplitude Coupling -- 1 Introduction -- 2 Materials and Methods -- 2.1 The LEEDUCA Dataset -- 2.2 Data Preprocessing -- 2.3 Phase-Amplitude Coupling -- 2.4 Visualization of Local PAC Patterns -- 3 Consistency of Temporal Patterns -- 4 Results and Discussion -- 5 Conclusions -- References -- Enhancing Neuronal Coupling Estimation by NIRS/EEG Integration -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset and Preprocessing -- 2.2 CFS Image Sequences -- 2.3 fNIRS Functional Activation -- 2.4 Classification -- 3 Results -- 4 Conclusions and Future Work -- References -- Causal Mechanisms of Dyslexia via Connectogram Modeling of Phase Synchrony -- 1 Introduction -- 2 Material and Methods -- 2.1 Data Acquisition -- 2.2 Preprocessing -- 2.3 Hilbert Transform -- 2.4 Granger Causality -- 2.5 Feature Selection -- 2.6 Connectograms -- 2.7 Machine Learning Classification -- 3 Results -- 4 Conclusions -- References -- Explainable Exploration of the Interplay Between HRV Features and EEG Local Connectivity Patterns in Dyslexia -- 1 Introduction -- 2 Materials and Methods -- 2.1 Database -- 2.2 Cross Frequency Coupling with ISPC -- 2.3 Heart Rate Variability Descriptors -- 2.4 Explainable Regression Experiments -- 3 Results -- 4 Discussion -- 5 Conclusion -- References.
Enhancing Intensity Differences in EEG Cross-Frequency Coupling Maps for Dyslexia Detection -- 1 Introduction -- 2 Materials and Methods -- 2.1 Database -- 2.2 Generation of CFC Maps from EEG Signals -- 2.3 Enhancing Differences in CFS Maps Through Histogram Transformation -- 2.4 Quantification of the Improvement -- 3 Results -- 4 Discussion and Conclusions -- References -- Improving Prediction of Mortality in ICU via Fusion of SelectKBest with SMOTE Method and Extra Tree Classifier -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 3.1 Dataset Used -- 3.2 Preprocessing -- 3.3 AutoML -- 4 Result and Discussion -- 5 Conclusion -- References -- A Cross-Modality Latent Representation for the Prediction of Clinical Symptomatology in Parkinson's Disease -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset and Preprocessing -- 2.2 Multi-modal Joint Latent Variable Model -- 2.3 Evaluation -- 3 Results and Discussion -- 4 Conclusions -- References -- Zero-Shot Ensemble of Language Models for Fine-Grain Mental-Health Topic Classification -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 4 Experiments and Results -- 5 Conclusions -- References -- Enhancing Interpretability in Machine Learning: A Focus on Genetic Network Programming, Its Variants, and Applications -- 1 Introduction -- 2 The Most Important Versions of GNP -- 2.1 Some Specific Applications of GNP Algorithm -- 3 Conclusion and Future Works -- References -- Enhancing Coronary Artery Disease Classification Using Optimized MLP Based on Genetic Algorithm -- 1 Introduction -- 2 Related Works -- 3 Materials and Methods -- 3.1 Dataset -- 3.2 Data Preprocessing -- 3.3 The Important Process of This Study -- 4 Results and Discussion -- 5 Conclusion -- References -- Extracting Heart Rate Variability from NIRS Signals for an Explainable Detection of Learning Disorders.
1 Introduction -- 2 Material and Methods -- 2.1 Participants -- 2.2 NIRS Acquisition -- 2.3 Extraction of Heart Signal from NIRS -- 2.4 Preprocessing -- 2.5 Classification and Explainability -- 3 Results -- 4 Conclusions and Future Work -- References -- Diagnosis of Parkinson Disease from EEG Signals Using a CNN-LSTM Model and Explainable AI -- 1 Introduction -- 2 Proposed Method -- 2.1 Dataset -- 2.2 Preprocessing -- 2.3 Deep Learning Model -- 3 Statistical Metrics -- 4 Experiment Results -- 5 Discussion, Conclusion, and Future Works -- References -- Early Diagnosis of Schizophrenia in EEG Signals Using One Dimensional Transformer Model -- 1 Introduction -- 2 Proposed Method -- 2.1 Dataset -- 2.2 Preprocessing -- 2.3 Feature Extraction Based on Transformer -- 2.4 Classification -- 3 Statistical Metrics -- 4 Experiment Results -- 5 Discussion, Conclusion, and Future Works -- References -- Diagnosis of Schizophrenia in EEG Signals Using dDTF Effective Connectivity and New PreTrained CNN and Transformer Models -- 1 Introduction -- 2 Proposed Method -- 2.1 Dataset -- 2.2 Preprocessing -- 2.3 Feature Extraction and Classification -- 3 Experiment Results -- 4 Discussion, Conclusion, and Future Works -- References -- A Survey on EEG Phase Amplitude Coupling to Speech Rhythm for the Prediction of Dyslexia -- 1 Introduction -- 2 Methods -- 2.1 Data Acquisition and Preprocessing -- 2.2 Cross-Frequency Coupling -- 2.3 Feature Aggregation and Classification -- 2.4 Evaluation and Interpretability -- 3 Results and Discussion -- 3.1 Best Performing Stimuli and PAC Measures -- 3.2 Effect of Classification Hyperparameters -- 3.3 Assymetric Differences Between DLX and CTL -- 4 Conclusions -- References -- Comprehensive Evaluation of Stroke Rehabilitation Dynamics: Integrating Brain-Computer Interface with Robotized Orthesic Hand and Longitudinal EEG Changes.
1 Introduction -- 2 Material and Methods -- 2.1 Participants -- 2.2 Description of the Experimentation -- 2.3 EEG Data Analysis -- 3 Results -- 3.1 Time Frequency -- 3.2 Topographic Maps -- 3.3 Power Bands -- 4 Discussion, Study Limitations and Future Work -- 5 Conclusion -- References -- PDBIGDATA: A New Database for Parkinsonism Research Focused on Large Models -- 1 Introduction -- 2 Database Description -- 3 Experiments and Results -- 4 Conclusions -- References -- A Comparative Study of Deep Learning Approaches for Cognitive Impairment Diagnosis Based on the Clock-Drawing Test -- 1 Introduction -- 2 Materials and Methods -- 2.1 CDT Databases -- 2.2 Image Preprocessing -- 2.3 Convolutional Neural Network -- 2.4 Attentive Pairwise Interaction Network -- 3 Experiments and Results -- 4 Discussion -- 5 Conclusion -- References -- Artificial Intelligence in Neurophysiology -- Prediction of Burst Suppression Occurrence Under General Anaesthesia Using Pre-operative EEG Signals -- 1 Introduction -- 2 Methods -- 2.1 Data -- 2.2 Pre-processing -- 2.3 Training -- 2.4 Models Evaluation -- 2.5 Generating Explanations with SHAP -- 3 Experiments -- 4 Results and Discussion -- 4.1 Models Evaluation -- 4.2 Explainability Analysis -- 4.3 Limitations and Future Work -- 5 Conclusion -- References -- Advances in Denoising Spikes Waveforms for Electrophysiological Recordings -- 1 Introduction -- 2 Methods -- 2.1 Acquisition System and Dataset -- 2.2 Neural Signal Denoising -- 2.3 Spike Sorting -- 2.4 Implementation Details -- 2.5 Software Testing -- 3 Results -- 3.1 Denoising and Spike Extraction Quality Measurement -- 4 Discussion -- 5 Conclusions -- References -- Analysis of Anxiety Caused by Fasting in Obesity Patients Using EEG Signals -- 1 Introduction -- 2 Materials and Methods -- 2.1 Subjects -- 2.2 Procedure -- 2.3 Data Processing -- 3 Results and Discussion.
4 Conclusions -- References -- Evolution of EEG Fractal Dimension Along a Sequential Finger Movement Task -- 1 Introduction: Fractal Dimension and its Application on EEG Signals Analysis -- 2 Materials and Methods -- 2.1 Dataset and Motor Task -- 2.2 EEG Signals Preprocessing -- 2.3 EMG Signals Preprocessing -- 2.4 Katz Fractal Dimension -- 2.5 KFD Time Windows -- 3 Results -- 4 Conclusion -- References -- Neuromotor and Cognitive Disorders -- Stress Classification Model Using Speech: An Ambulatory Protocol-Based Database Study -- 1 Introduction -- 2 Methods -- 2.1 Database -- 2.2 Feature Extraction -- 2.3 Supervised Classification -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Exploring Spatial Cognition: Comparative Analysis of Agent-Based Models in Dynamic and Static Environments -- 1 Introduction -- 2 Methodology -- 2.1 EvoJAX -- 2.2 Materials and Method -- 2.3 Results -- 3 Conclusions and Future Directions -- References -- Machine Learning for Personality Type Classification on Textual Data -- 1 Introduction -- 2 Background -- 3 Materials and Methods -- 3.1 Data Collection: -- 3.2 Feature Extraction -- 3.3 Target Classes -- 3.4 Classification Models -- 3.5 Performance Evaluation Metrics -- 4 Results -- 5 Conclusions -- References -- Grad-CAM Applied to the Detection of Instruments Used in Facial Presentation Attacks -- 1 Introduction -- 2 Related Work and Background -- 2.1 PAD Techniques -- 2.2 XAI Techniques -- 3 Methods and Materials -- 3.1 Design and Implementation -- 3.2 eXpainable Artificial Intelligence Grad-CAM -- 3.3 Procediment -- 3.4 Statistical Analysis -- 3.5 Database -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- Comparison of an Accelerated Garble Embedding Methodology for Privacy Preserving in Biomedical Data Analytics -- 1 Introduction -- 1.1 State of the Art -- 2 Theoretical Framework.
2.1 Information Comparison.
Record Nr. UNINA-9910865264203321
Ferrández Vicente José Manuel  
Cham : , : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Bioinspired Systems for Translational Applications : 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024, Olhâo, Portugal, June 4-7, 2024, Proceedings, Part II
Bioinspired Systems for Translational Applications : 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024, Olhâo, Portugal, June 4-7, 2024, Proceedings, Part II
Autore Ferrández Vicente José Manuel
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer, , 2024
Descrizione fisica 1 online resource (553 pages)
Altri autori (Persone) Val CalvoMikel
AdeliHojjat
Collana Lecture Notes in Computer Science Series
ISBN 3-031-61137-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Machine Learning in Computer Vision and Robotics -- Unsupervised Detection of Incoming and Outgoing Traffic Flows in Video Sequences -- 1 Introduction -- 2 Methodology -- 3 Experimental Results -- 3.1 Methods -- 3.2 Datasets -- 3.3 Results -- 4 Conclusions -- References -- A Decentralized Collision Avoidance Algorithm for Individual and Collaborative UAVs -- 1 Introduction -- 2 State of Art -- 3 Methodology -- 3.1 Collision Avoidance -- 3.2 System Formation -- 4 Experiments and Results -- 5 Conclusions -- References -- Improved Surface Defect Classification from a Simple Convolutional Neural Network by Image Preprocessing and Data Augmentation -- 1 Introduction -- 2 Materials -- 2.1 The NEU Dataset -- 2.2 Image Preprocessing -- 2.3 Data Augmentation -- 3 Methodology -- 3.1 Simple Convolutional Neural Network -- 3.2 Training Strategy -- 4 Results and Discussion -- 5 Conclusions -- References -- Prediction of Optimal Locations for 5G Base Stations in Urban Environments Using Neural Networks and Satellite Image Analysis -- 1 Introduction -- 2 Methodology -- 2.1 Segmentation of Satellite Images -- 2.2 Base Station Deployment -- 3 Experiments -- 3.1 Convolutional Neural Networks -- 3.2 Dataset -- 3.3 Evaluation -- 3.4 Results -- 4 Conclusions -- References -- Enhanced Cellular Detection Using Convolutional Neural Networks and Sliding Window Super-Resolution Inference*-6pt -- 1 Introduction -- 2 Methodology -- 3 Experiments -- 3.1 Dataset -- 3.2 Super-Resolution Model -- 3.3 Object Detection Models -- 3.4 Results -- 4 Conclusions and Future Lines -- References -- Exploring Text-Driven Approaches for Online Action Detection -- 1 Introduction -- 2 Related Works -- 2.1 Online Action Detection -- 2.2 Vision-Language Models -- 3 Methodology -- 4 Experiments.
4.1 Experimental Setup -- 4.2 Zero-Shot/Few-Shot Action Detection -- 4.3 Comparison with State-of-the-Art Methods -- 5 Conclusion -- References -- Deep Learning for Assistive Decision-Making in Robot-Aided Rehabilitation Therapy -- 1 Introduction -- 2 Materials and Methods -- 2.1 Subjects -- 2.2 Experimental Setup and Data Collection -- 2.3 Data Processing -- 2.4 Model Architecture -- 3 Results and Discussion -- 4 Conclusion -- References -- Text-Driven Data Augmentation Tool for Synthetic Bird Behavioural Generation -- 1 Introduction -- 2 Related Works -- 2.1 Birds Datasets -- 2.2 Generative Models -- 3 Synthetic Video Generation -- 3.1 Enhancing Captions -- 3.2 Generative Video Models -- 4 Results -- 5 Conclusions -- References -- Deep Learning for Enhanced Risk Assessment in Home Environments -- 1 Introduction -- 2 Related Work -- 2.1 Risks Assessment -- 2.2 Object Detection -- 2.3 Video Captioning -- 3 Methodology -- 3.1 Objects Extraction -- 3.2 Risks Identification -- 4 Experiments -- 4.1 Setup and Data -- 4.2 Results -- 5 Conclusion -- References -- Lightweight CNNs for Advanced Bird Species Recognition on the Edge -- 1 Introduction -- 2 Related Works -- 2.1 Bird Species Recognition -- 2.2 Edge Computing -- 3 Methodology -- 3.1 Datasets -- 3.2 Training -- 4 Experiments -- 4.1 Setup -- 4.2 Results -- 5 Conclusion -- References -- Learning Adaptable Utility Models for Morphological Diversity -- 1 Introduction -- 2 Motivational System for Open-Ended Learning -- 2.1 Novelty-Based Intrinsic Motivation. Enhancing Exploration -- 2.2 Frustration-Based Intrinsic Motivation. Preventing Learning Stagnation -- 3 Deliberative Decision-Making with World and Utility Models -- 3.1 World Model Learning -- 3.2 Utility Model Learning -- 4 Experimental Setup: EMERGE Robot -- 5 Experimental Results -- 6 Conclusion -- References.
Deep Learning-Based Classification of Invasive Coronary Angiographies with Different Patch-Generation Techniques -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 2.2 Data Preprocessing -- 3 Experimental Results -- 3.1 Training and Experiments Description -- 3.2 Results -- 4 Conclusions -- References -- Bio-inspired Computing Approaches -- Refinement of Protein Structures with a Memetic Algorithm. Examples with SARS-CoV-2 Proteins -- 1 Introduction -- 2 Methods -- 2.1 Rosetta Relax Process -- 2.2 Relax-DE -- 3 Results -- 3.1 Setup of the Refinement Approaches -- 3.2 Refinement of Predicted Structures -- 4 Conclusions -- References -- Evolutionary Algorithms for Bin Packing Problem with Maximum Lateness and Waste Minimization -- 1 Introduction -- 2 Problem Definition -- 3 The Solution Method -- 4 Evolutionary Algorithms -- 4.1 Genetic Programming -- 4.2 Genetic Algorithm -- 5 Experimental Analysis -- 5.1 Set up -- 5.2 Results -- 6 Conclusions and Future Work -- References -- Stationary Wavelet Entropy and Cat Swarm Optimization to Detect COVID-19 -- 1 Introduction -- 2 Background -- 3 Dataset -- 4 Methodology -- 4.1 Feed-Forward Neural Network -- 4.2 Stationary Wavelet Entropy -- 4.3 Cat Swarm Optimization -- 4.4 K-Fold Cross-Validation -- 4.5 Evaluation -- 5 Experiment and Discussion -- 5.1 Statistical Evaluation -- 5.2 Comparison to State-of-the-Art Methods -- 5.3 ROC Curve -- 6 Conclusion and Future Research -- References -- Private Inference on Layered Spiking Neural P Systems -- 1 Introduction -- 2 Related Work -- 3 Layered Spiking Neural P Systems -- 4 Private Inference -- 4.1 The Protocol -- 4.2 Security Discussion -- 5 Conclusions and Further Directions of Research -- References -- Cooperative Multi-fitness Evolutionary Algorithm for Scientific Workflows Scheduling -- 1 Introduction -- 2 The Scientific Workflow Scheduling Model.
2.1 Workflow Scheduling Problem Overview -- 3 Overview of the Genetic Algorithm Approach -- 4 Cooperative Multi-fitness Functions Evaluation -- 5 Experimental Study -- 5.1 Benchmark Instances -- 5.2 Benchmark Platform -- 5.3 Efficiency of the Cooperative Multi-fitness Approach -- 6 Conclusion -- References -- A Genetic Approach to Green Flexible Job Shop Problem Under Uncertainty -- 1 Introduction -- 2 Problem Definition -- 3 Solving Methodology -- 4 Experimental Results -- 5 Conclusion -- References -- Social and Civil Engineering Through Human AI Translations -- AI Emmbedded in Drone Control -- 1 Introduction -- 2 Drone Operations Supported by AI Algorithms -- 2.1 Delivery Systems -- 2.2 Optimization and Complexity Associated with Cargo and Resources -- 2.3 Emergency Situations -- 2.4 Drone Identification and Detection -- 2.5 Flight Control and Safety -- 2.6 Agricultural Operations -- 3 Conclusions and Future Work -- References -- Dual-System Recommendation Architecture for Adaptive Reading Intervention Platform for Dyslexic Learners -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data and Exploratory Analysis -- 2.2 Description of the Intervention Trial -- 2.3 Word Generator -- 2.4 Embedded Intra/Inter-user Recommender Engines -- 2.5 Surmounting Cold Start and Limited Data Hurdles -- 3 Results -- 4 Conclusions -- References -- Accurate LiDAR-Based Semantic Classification for Powerline Inspection -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Online Segmentation -- 3.2 Full Map Refinement -- 4 Validation -- 5 Conclusions -- References -- RESISTO Project: Automatic Detection of Operation Temperature Anomalies for Power Electric Transformers Using Thermal Imaging -- 1 Introduction -- 1.1 Introduction to the RESISTO Project -- 1.2 Mitigating Transformer Risks in Electricity Networks -- 2 Materials and Methods.
2.1 Thermographic Data Acquisition -- 2.2 Thermal Anomalies Detection System -- 2.3 Synthetic Data Generation -- 3 Results and Discussion -- 3.1 Simulation Results -- 3.2 Registered Temperature Time Series -- 4 Conclusions -- References -- RESISTO Project: Safeguarding the Power Grid from Meteorological Phenomena -- 1 Introduction -- 1.1 Objectives -- 1.2 Project Innovations -- 2 Proposed Solution -- 2.1 Electrical Resilience Platform: GridWatch -- 2.2 Automatic Detection of Operation Temperature Anomalies Using Thermal Imaging -- 2.3 Fleet of Drones -- 3 Discussion -- 4 Conclusions -- References -- Multi-UAV System for Power-Line Failure Detection Within the RESISTO Project -- 1 Introduction -- 2 System Description -- 2.1 Planner Description -- 2.2 Software Implementation -- 2.3 Hardware Implementation -- 3 Validation -- 3.1 Planning Approach Simulation -- 3.2 Test Flights -- 4 Conclusions and Future Works -- References -- Smart Renewable Energies: Advancing AI Algorithms in the Renewable Energy Industry -- Machine Learning Health Estimation for Lithium-Ion Batteries Under Varied Conditions -- 1 Introduction -- 2 Methods -- 2.1 Experimental Design and Data Processing -- 3 Results and Discussion -- 4 Conclusions -- References -- Energy Flux Prediction Using an Ordinal Soft Labelling Strategy -- 1 Introduction -- 2 Data Description and Processing -- 2.1 Buoys Measurements and Reanalysis Data -- 2.2 Obtaining Ordinal Labels -- 3 Experimental Settings -- 3.1 Compared Methodologies -- 3.2 Model Training -- 4 Results and Discussion -- 5 Conclusions -- References -- Medium- and Long-Term Wind Speed Prediction Using the Multi-task Learning Paradigm -- 1 Introduction -- 2 Data Description -- 2.1 Wind Speed Data -- 2.2 Predictive Variables -- 3 Multi-task Artificial Neural Networks -- 4 Experimental Settings -- 5 Results and Discussion -- 6 Conclusions.
References.
Record Nr. UNISA-996601560803316
Ferrández Vicente José Manuel  
Cham : , : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Bioinspired Systems for Translational Applications : 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024, Olhâo, Portugal, June 4-7, 2024, Proceedings, Part II
Bioinspired Systems for Translational Applications : 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024, Olhâo, Portugal, June 4-7, 2024, Proceedings, Part II
Autore Ferrández Vicente José Manuel
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer, , 2024
Descrizione fisica 1 online resource (553 pages)
Altri autori (Persone) Val CalvoMikel
AdeliHojjat
Collana Lecture Notes in Computer Science Series
ISBN 3-031-61137-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Machine Learning in Computer Vision and Robotics -- Unsupervised Detection of Incoming and Outgoing Traffic Flows in Video Sequences -- 1 Introduction -- 2 Methodology -- 3 Experimental Results -- 3.1 Methods -- 3.2 Datasets -- 3.3 Results -- 4 Conclusions -- References -- A Decentralized Collision Avoidance Algorithm for Individual and Collaborative UAVs -- 1 Introduction -- 2 State of Art -- 3 Methodology -- 3.1 Collision Avoidance -- 3.2 System Formation -- 4 Experiments and Results -- 5 Conclusions -- References -- Improved Surface Defect Classification from a Simple Convolutional Neural Network by Image Preprocessing and Data Augmentation -- 1 Introduction -- 2 Materials -- 2.1 The NEU Dataset -- 2.2 Image Preprocessing -- 2.3 Data Augmentation -- 3 Methodology -- 3.1 Simple Convolutional Neural Network -- 3.2 Training Strategy -- 4 Results and Discussion -- 5 Conclusions -- References -- Prediction of Optimal Locations for 5G Base Stations in Urban Environments Using Neural Networks and Satellite Image Analysis -- 1 Introduction -- 2 Methodology -- 2.1 Segmentation of Satellite Images -- 2.2 Base Station Deployment -- 3 Experiments -- 3.1 Convolutional Neural Networks -- 3.2 Dataset -- 3.3 Evaluation -- 3.4 Results -- 4 Conclusions -- References -- Enhanced Cellular Detection Using Convolutional Neural Networks and Sliding Window Super-Resolution Inference*-6pt -- 1 Introduction -- 2 Methodology -- 3 Experiments -- 3.1 Dataset -- 3.2 Super-Resolution Model -- 3.3 Object Detection Models -- 3.4 Results -- 4 Conclusions and Future Lines -- References -- Exploring Text-Driven Approaches for Online Action Detection -- 1 Introduction -- 2 Related Works -- 2.1 Online Action Detection -- 2.2 Vision-Language Models -- 3 Methodology -- 4 Experiments.
4.1 Experimental Setup -- 4.2 Zero-Shot/Few-Shot Action Detection -- 4.3 Comparison with State-of-the-Art Methods -- 5 Conclusion -- References -- Deep Learning for Assistive Decision-Making in Robot-Aided Rehabilitation Therapy -- 1 Introduction -- 2 Materials and Methods -- 2.1 Subjects -- 2.2 Experimental Setup and Data Collection -- 2.3 Data Processing -- 2.4 Model Architecture -- 3 Results and Discussion -- 4 Conclusion -- References -- Text-Driven Data Augmentation Tool for Synthetic Bird Behavioural Generation -- 1 Introduction -- 2 Related Works -- 2.1 Birds Datasets -- 2.2 Generative Models -- 3 Synthetic Video Generation -- 3.1 Enhancing Captions -- 3.2 Generative Video Models -- 4 Results -- 5 Conclusions -- References -- Deep Learning for Enhanced Risk Assessment in Home Environments -- 1 Introduction -- 2 Related Work -- 2.1 Risks Assessment -- 2.2 Object Detection -- 2.3 Video Captioning -- 3 Methodology -- 3.1 Objects Extraction -- 3.2 Risks Identification -- 4 Experiments -- 4.1 Setup and Data -- 4.2 Results -- 5 Conclusion -- References -- Lightweight CNNs for Advanced Bird Species Recognition on the Edge -- 1 Introduction -- 2 Related Works -- 2.1 Bird Species Recognition -- 2.2 Edge Computing -- 3 Methodology -- 3.1 Datasets -- 3.2 Training -- 4 Experiments -- 4.1 Setup -- 4.2 Results -- 5 Conclusion -- References -- Learning Adaptable Utility Models for Morphological Diversity -- 1 Introduction -- 2 Motivational System for Open-Ended Learning -- 2.1 Novelty-Based Intrinsic Motivation. Enhancing Exploration -- 2.2 Frustration-Based Intrinsic Motivation. Preventing Learning Stagnation -- 3 Deliberative Decision-Making with World and Utility Models -- 3.1 World Model Learning -- 3.2 Utility Model Learning -- 4 Experimental Setup: EMERGE Robot -- 5 Experimental Results -- 6 Conclusion -- References.
Deep Learning-Based Classification of Invasive Coronary Angiographies with Different Patch-Generation Techniques -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 2.2 Data Preprocessing -- 3 Experimental Results -- 3.1 Training and Experiments Description -- 3.2 Results -- 4 Conclusions -- References -- Bio-inspired Computing Approaches -- Refinement of Protein Structures with a Memetic Algorithm. Examples with SARS-CoV-2 Proteins -- 1 Introduction -- 2 Methods -- 2.1 Rosetta Relax Process -- 2.2 Relax-DE -- 3 Results -- 3.1 Setup of the Refinement Approaches -- 3.2 Refinement of Predicted Structures -- 4 Conclusions -- References -- Evolutionary Algorithms for Bin Packing Problem with Maximum Lateness and Waste Minimization -- 1 Introduction -- 2 Problem Definition -- 3 The Solution Method -- 4 Evolutionary Algorithms -- 4.1 Genetic Programming -- 4.2 Genetic Algorithm -- 5 Experimental Analysis -- 5.1 Set up -- 5.2 Results -- 6 Conclusions and Future Work -- References -- Stationary Wavelet Entropy and Cat Swarm Optimization to Detect COVID-19 -- 1 Introduction -- 2 Background -- 3 Dataset -- 4 Methodology -- 4.1 Feed-Forward Neural Network -- 4.2 Stationary Wavelet Entropy -- 4.3 Cat Swarm Optimization -- 4.4 K-Fold Cross-Validation -- 4.5 Evaluation -- 5 Experiment and Discussion -- 5.1 Statistical Evaluation -- 5.2 Comparison to State-of-the-Art Methods -- 5.3 ROC Curve -- 6 Conclusion and Future Research -- References -- Private Inference on Layered Spiking Neural P Systems -- 1 Introduction -- 2 Related Work -- 3 Layered Spiking Neural P Systems -- 4 Private Inference -- 4.1 The Protocol -- 4.2 Security Discussion -- 5 Conclusions and Further Directions of Research -- References -- Cooperative Multi-fitness Evolutionary Algorithm for Scientific Workflows Scheduling -- 1 Introduction -- 2 The Scientific Workflow Scheduling Model.
2.1 Workflow Scheduling Problem Overview -- 3 Overview of the Genetic Algorithm Approach -- 4 Cooperative Multi-fitness Functions Evaluation -- 5 Experimental Study -- 5.1 Benchmark Instances -- 5.2 Benchmark Platform -- 5.3 Efficiency of the Cooperative Multi-fitness Approach -- 6 Conclusion -- References -- A Genetic Approach to Green Flexible Job Shop Problem Under Uncertainty -- 1 Introduction -- 2 Problem Definition -- 3 Solving Methodology -- 4 Experimental Results -- 5 Conclusion -- References -- Social and Civil Engineering Through Human AI Translations -- AI Emmbedded in Drone Control -- 1 Introduction -- 2 Drone Operations Supported by AI Algorithms -- 2.1 Delivery Systems -- 2.2 Optimization and Complexity Associated with Cargo and Resources -- 2.3 Emergency Situations -- 2.4 Drone Identification and Detection -- 2.5 Flight Control and Safety -- 2.6 Agricultural Operations -- 3 Conclusions and Future Work -- References -- Dual-System Recommendation Architecture for Adaptive Reading Intervention Platform for Dyslexic Learners -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data and Exploratory Analysis -- 2.2 Description of the Intervention Trial -- 2.3 Word Generator -- 2.4 Embedded Intra/Inter-user Recommender Engines -- 2.5 Surmounting Cold Start and Limited Data Hurdles -- 3 Results -- 4 Conclusions -- References -- Accurate LiDAR-Based Semantic Classification for Powerline Inspection -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Online Segmentation -- 3.2 Full Map Refinement -- 4 Validation -- 5 Conclusions -- References -- RESISTO Project: Automatic Detection of Operation Temperature Anomalies for Power Electric Transformers Using Thermal Imaging -- 1 Introduction -- 1.1 Introduction to the RESISTO Project -- 1.2 Mitigating Transformer Risks in Electricity Networks -- 2 Materials and Methods.
2.1 Thermographic Data Acquisition -- 2.2 Thermal Anomalies Detection System -- 2.3 Synthetic Data Generation -- 3 Results and Discussion -- 3.1 Simulation Results -- 3.2 Registered Temperature Time Series -- 4 Conclusions -- References -- RESISTO Project: Safeguarding the Power Grid from Meteorological Phenomena -- 1 Introduction -- 1.1 Objectives -- 1.2 Project Innovations -- 2 Proposed Solution -- 2.1 Electrical Resilience Platform: GridWatch -- 2.2 Automatic Detection of Operation Temperature Anomalies Using Thermal Imaging -- 2.3 Fleet of Drones -- 3 Discussion -- 4 Conclusions -- References -- Multi-UAV System for Power-Line Failure Detection Within the RESISTO Project -- 1 Introduction -- 2 System Description -- 2.1 Planner Description -- 2.2 Software Implementation -- 2.3 Hardware Implementation -- 3 Validation -- 3.1 Planning Approach Simulation -- 3.2 Test Flights -- 4 Conclusions and Future Works -- References -- Smart Renewable Energies: Advancing AI Algorithms in the Renewable Energy Industry -- Machine Learning Health Estimation for Lithium-Ion Batteries Under Varied Conditions -- 1 Introduction -- 2 Methods -- 2.1 Experimental Design and Data Processing -- 3 Results and Discussion -- 4 Conclusions -- References -- Energy Flux Prediction Using an Ordinal Soft Labelling Strategy -- 1 Introduction -- 2 Data Description and Processing -- 2.1 Buoys Measurements and Reanalysis Data -- 2.2 Obtaining Ordinal Labels -- 3 Experimental Settings -- 3.1 Compared Methodologies -- 3.2 Model Training -- 4 Results and Discussion -- 5 Conclusions -- References -- Medium- and Long-Term Wind Speed Prediction Using the Multi-task Learning Paradigm -- 1 Introduction -- 2 Data Description -- 2.1 Wind Speed Data -- 2.2 Predictive Variables -- 3 Multi-task Artificial Neural Networks -- 4 Experimental Settings -- 5 Results and Discussion -- 6 Conclusions.
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Record Nr. UNINA-9910865263403321
Ferrández Vicente José Manuel  
Cham : , : Springer, , 2024
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