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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 / / edited by José Manuel Ferrández Vicente, Mikel Val Calvo, Hojjat Adeli
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 / / edited by José Manuel Ferrández Vicente, Mikel Val Calvo, Hojjat Adeli
Autore Ferrández Vicente José Manuel
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (560 pages)
Disciplina 40,151
Altri autori (Persone) Val CalvoMikel
AdeliHojjat
Collana Lecture Notes in Computer Science
Soggetto topico Computer science
Computer networks
Artificial intelligence
Image processing - Digital techniques
Computer vision
Social sciences - Data processing
Theory of Computation
Computer Communication Networks
Artificial Intelligence
Computer Imaging, Vision, Pattern Recognition and Graphics
Computer Application in Social and Behavioral Sciences
Intel·ligència artificial
Visió per ordinador
Processament digital d'imatges
Xarxes d'ordinadors
Teoria de la computació
Soggetto genere / forma Congressos
Llibres electrònics
ISBN 9783031611407
3031611403
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Machine learning in neuroscience -- artificial intelligence in neurophysiology -- neuromotor and cognitive disorders -- intelligent systems for assessment, treatment, and assistance in early stages of Alzheimer's disease and other dementias -- socio-cognitive, affective and physiological computing -- affective computing and context awareness in ambientintelliigence -- learning tools to lecture.
Record Nr. UNINA-9910865264203321
Ferrández Vicente José Manuel  
Cham : , : Springer Nature Switzerland : , : Imprint : 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: From Robotics to Social Engineering : 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024, Olhâo, Portugal, June 4–7, 2024, Proceedings, Part II / / edited by José Manuel Ferrández Vicente, Mikel Val Calvo, Hojjat Adeli
Bioinspired Systems for Translational Applications: From Robotics to Social Engineering : 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024, Olhâo, Portugal, June 4–7, 2024, Proceedings, Part II / / edited by José Manuel Ferrández Vicente, Mikel Val Calvo, Hojjat Adeli
Autore Ferrández Vicente José Manuel
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (553 pages)
Disciplina 40,151
Altri autori (Persone) Val CalvoMikel
AdeliHojjat
Collana Lecture Notes in Computer Science
Soggetto topico Computer science
Computer networks
Artificial intelligence
Image processing - Digital techniques
Computer vision
Social sciences - Data processing
Theory of Computation
Computer Communication Networks
Artificial Intelligence
Computer Imaging, Vision, Pattern Recognition and Graphics
Computer Application in Social and Behavioral Sciences
ISBN 9783031611377
3031611373
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Machine learning in computer vision and robotics -- bio-inspired computing approaches -- social and civil engineering through human AI translations -- smart renewable energies: advancing AI algorithms in the renewable energy industry -- bioinspired applications.
Record Nr. UNINA-9910865263403321
Ferrández Vicente José Manuel  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui