This book provides an overview on the current progresses in artificial intelligence and neural nets in data science. The book is reporting on intelligent algorithms and applications modeling, prediction, and recognition tasks and many other application areas supporting complex multimodal systems to enhance and improve human–machine or human–human interactions. This field is broadly addressed by the scientific communities and has a strong commercial impact since investigates on the theoretical frameworks supporting the implementation of sophisticated computational intelligence tools. Such tools will support multidisciplinary aspects of data mining and data processing characterizing appropriate system reactions to human-machine interactional exchanges in interactive scenarios. The emotional issue has recently gained increasing attention for such complex systems due to its relevance in helping in the most common human tasks (like cognitive processes, perception, learning, communication, and even "rational" decision-making) and therefore improving the quality of life of the end users
Author(s): Anna Esposito; Marcos Faundez-Zanuy; Francesco Carlo Morabito; Eros Pasero
Publisher: Springer Nature Singapore
Year: 2023
Language: English
Pages: 358
Cover
Front Matter
Part I. Neural Networks and Related Applications
1. Generating New Sounds by Vector Arithmetic in the Latent Space of the MelGAN Architecture
2. Graph Neural Networks for Topological Feature Extraction in ECG Classification
3. Manifold Learning by a Deep Gaussian Process Variational Autoencoder
4. Analysis of Sensors for Movement Analysis
5. Dual Deep Clustering
6. Learning-Based Approach to Predict Fatal Events in Brugada Syndrome
7. Breast Cancer Localization and Classification in Mammograms Using YoloV5
8. Deep Acoustic Emission Detection Trained on Seismic Signals
9. A Deep Learning Framework for the Classification of Pre-prodromal and Prodromal Alzheimer’s Disease Using Resting-State EEG Signals
10. Imitation Learning Through Prior Injection in Markov Decision Processes
11. Vision-Based Human Activity Recognition Methods Using Pose Estimation
12. Identifying Exoplanets in TESS Data by Deep Learning
13. Computational Intelligence for Marine Litter Recovery
14. A Synthetic Dataset for Learning Optical Flow in Underwater Environment
15. BERT Classifies SARS-CoV-2 Variants
16. Competence-Based Coalition Choice, a Non-additive Approach
17. Forecasting Mortality with Autoencoders: An Application to Italian Mortality Data
18. Leaky Echo State Network for Audio Classification in Construction Sites
19. ECG Signal Classification Using Long Short-Term Memory Neural Networks
20. A Convolutional Neural Network Approach for the Classification of Subjects with Epileptic Seizures Versus Psychogenic Non-epileptic Seizures and Control, Based on Automatic Feature Extraction from Empirical Mode Decomposition of Interictal EEG Recordings
21. Commerce Districts: Conditions for Customer Overall Satisfaction in a Multi-attribute Framework
22. Problematic Merging and Cartels: A Collusion Risk Factors Analysis
Part II. Dynamics of Signal Exchanges and Empathic Systems
23. Conversational Ontologies for Human–Machine Interaction: Application for Cultural Heritage
24. On Statistical Prediction of Geometric Features of Three-Dimensional Configurations of Proteins I: Theoretical Description of an Inference Method
25. Emotion Recognition in Preschool Children: The Role of Age, Gender and Emotional Categories
26. A Multilevel Approach on the Investigation of the Association Between Responses to Infant Cues and Caregiving Propensity
27. What Would Happen if Hackers Attacked the Railways? Consideration of the Need for Ethical Codes in the Railway Transport Systems
28. Home Automation and Applied Behavior Analysis: Mand’s Development in the Natural Environment
29. The Role of HEXACO Personality Traits on Predicting Problematic and Risky Behaviors in Adolescents
30. Evolving Aggregation Behaviors in Swarms from an Evolutionary Algorithms Point of View
31. A Review of the Use of Neural Models of Language and Conversation to Support Mental Health
32. Generative Adversarial Networks in Federated Learning
33. Identifying Key Physical and Natural Environmental Correlates of Child Development: An Exploratory Study Using Machine Learning on Data from Pakistan
