Description
Book Synopsis.- Explainable and Interpretable Machine Learning (xAI) with a Focus on Applications.
.- Understanding of Latent spaces in a battery aging prediction model through eXplainable AI.
.- Exploring brain lateralization using Tensor decomposition of EEG phase-amplitude coupling.
.- Ethical Considerations in Artificial Intelligence and Machine Learning.
.- Kolmogorov-Arnold Networks for the Development of Intrusion Detection Systems.
.- General Applications of AI.
.- Machine Learning based Screening for Psychological Distress using a Perceived Control Mobile App.
.- Tobacco and Weed Segmentation from Remote Images Using Artificial Intelligence.
.- A Hybrid ResNet50-LSTM Architecture for Video Sentiment Analysis.
.- Towards a Framework that facilitates the Construction of Image Segmentation Models.
.- TASER-Net: Transformer Based Speech Emotion Recognition.
.- Experimental Analysis and Modeling of Electrochemical Oxygen Pump Cell ECOpump.
.- Empowering Scalable Fraud Detection Using Graph Neural Networks and Incremental Learning.
.- Transfer Learning approach for prediction of maximum wave height in two locations of the Bay of Biscay: Bilbao and Cabo de Pe˜nas.
.- Classifier fusion for the detection of defects from active thermography.
.- Multimodal analysis of neuropsychological tests from EEG and fMRI data.
.- Solid-waste Classification Using Deep Learning Fusion Model.
.- Improving PV power prediction based on GRU and meteorological factors.
.- Poisson Hamiltonian Neural Networks: Structure-Preserving Learning of Dynamical Systems.
.- SEF-Net: A Hybrid Deep Learning Architecture for Multi-Step Forecasting in Sustainable Energy Markets.
.- A new approach to detecting occupational diseases using time series.
.- Comparative Analysis of Spiking Neurons Mathematical Models Training using Surrogate Gradients Techniques.
.- ITOMAD – Intelligent Techniques for Optimization, Modeling, and Anomaly Detection.
.- Design and Capture of a 5G SA Traffic Dataset Under Jamming Conditions.
.- Predicting TiO2 and FeO Concentrations in Lunar Regolith Using Machine Learning Models: A Spectral Reflectance Approach.
.- Optimal malware mitigation in IoT networks: A comparative study of Neural ODEs and Pontryagin’s maximum principle.
.- Study on the Impact of Low-Cost Sensor Alternatives for Photovoltaic Panel Modelling in Smart Grid Applications.
.- A Short Analysis of Hybrid Frameworks Based on Self-Organizing Maps to Improve Traditional Systems.
.- Comparative Performance of Convolutional Neural Networks and Vision Transformers for Quality Assurance of a Welding Process.
.- A Novel Indicator for Nitrogen Prediction in Wastewater Treatment Plants. Implementation of Intelligent Agent-Based.
.- Power Prediction System for Photovoltaic Panels Using Artificial Intelligence.
.- Towards safer hydrogen infrastructure: anomaly detection in synthetic hydrogen dispensing data.
.- Machine Learning for 4.0 Industry Solutions.
.- Physics Informed Machine Learning for Power Flow Analysis: Injecting Knowledge via Pre-, In-, and Post-Processing.
.- Dimensionality Reduction and Outlier Analysis for the NF-ToN-IoT Cybersecurity Dataset.
.- Data-Driven All-Optical Magnetometry: A Comparative Evaluation of Regression Models Using NV Center Fluorescence Lifetimes.
.- Smart Incident Prediction from NOC Alert Events in Digital TV Broadcasting Networks.
.- Machine Learning for Photovoltaic System Optimization and Control in Modern Energy Grids.
.- Symmetrical Current Flow Reconstruction for Sector-shaped Multi-Wire Cables using Machine Learning.
.- Comparison of Multiclass Classification on Impedance Spectra to Estimate the State of Charge of Zinc-Air Batteries.
.- Edge Machine Learning for All-Optical Fluorescence Lifetime-Based Sensing With NV Centers.
.- Evaluating LSTM Model Performance for Solar Energy Prediction Using Real vs. Forecasted Exogenous Weather Data.
.- Computational Approaches for Resolving the Low-Field Ambiguity in All-Optical Magnetic Field Sensing With NV Centers.
.- Improved Post Processing Model for Photovoltaic Power Forecasting based on Clustering.
.- New and future advances in BCI-based Spellers.
.- An event-related potential BCI speller using a wearable, single-channel EEG headset with electrodes on the forehead.
.- A Framework for Controlling NV Centers with OPX+: Design, Implementation, and Applications.
.- Exploring Code-Modulated Visual Evoked Potentials Spellers in Realistic Scenarios.
.- Towards Secure Transaction Authentication Using a cVEP-Based BCI.
.- Evaluating Color Heterogeneity in RSVP-Based ERP-BCIs.
.- Graph-Attentive CNN for cVEP-BCI with Insights into Electrode Significance.
.- BCI with Intuitive Object Control based on Code-Modulated Visual Evoked Potentials.
.- Exploring the integration of c-VEP-based BCI spellers in mixed reality: a pilot study.
.- Social and Ethical aspects of AI.
.- Quantitative and qualitative evaluation on local explainability models for anomaly detection algorithms.
.- Bias and Fairness in NLP: Addressing Social and Cultural Biases.
.- Trustworthy AI Benchmark for Responsible Smart Grid as Critical Infrastructure.
.- TextNet: End-to-End Deep Learning Framework for Dynamic and Contextually Aware Text Clustering.
.- Implications of Human+Machine Systems as Critical Infrastructures under Sustainable Development Goals.
