This book constitutes the refereed proceedings of the 25th International Conference on Engineering Applications of Neural Networks, EANN 2024, held in Corfu, Greece, during June 27-30, 2024. The 41 full and 2 short papers included in this book were carefully reviewed and selected from 85 submissions. convolutional neural networks.

Deep Learning.- Active Learning with Aggregated Uncertainties from Image AugmentationsAn Approach to Predict Optimal Configurations for LDA-based Topic Modeling.- An Autoencoder-based approach for Anomaly Detection of Machining Processes using Acoustic Emission signals.- An EANN-Based Recommender System for Drug RecommendationAutomation of the error-prone PAM-4 sequence discovery for the purpose of high-speed serial receiver testing using reinforcement learning methods.- Binary Black Hole Parameter Estimation from Gravitational Waves with Deep Learning MethodsComparative Analysis of Large Language Models in Structured Information Extraction from Job Postings.- Comparative study between Q-NAS and traditional CNNs for Brain Tumor classification.- Deep Echo State Networks for modelling of industrial systems.- Empirical Insights into Deep Learning Models for Misinformation Classification within Constrained Data EnvironmentEnhancing Bandwidth Efficiency for Video Motion Transfer Applications using Deep Learning Based Keypoint Prediction.- Enhancing Natural Language Query to SQL Query Generation through  Classification-Based Table SelectionExploiting LMM-based knowledge for image classification tasks.- HEADS: Hybrid Ensemble Anomaly Detection System for Internet-of-Things NetworksHEDL-IDS2: An Innovative Hybrid Ensemble Deep Learning Prototype for Cyber Intrusion DetectionIntelligent framework for monitoring student emotions during online learning.- Leveraging Diverse Data Sources for Enhanced Prediction of Severe Weather-Related Disruptions Across Different Time Horizons.- Machine Learning-Based Detection and Classification of Neurodevelopmental Disorders from Speech Patterns.- Neural SDE-based Epistemic Uncertainty Quantification in Deep Neural Networks.- Robust Traffic Prediction using Probabilistic Spatio-temporal Graph Convolutional Network.- Support Vector Based Anomaly Detection in Federated LearningTowards Digitisation of Technical Drawings in Architecture:  Evaluation of CNN Classification on the Perdaw DatasetYOLOv5 and Residual Network for Intelligent Text Recognition on Degraded Serial Number Plates.- Neural Networks.- A Spike Vision Approach for Multi-Object Detection and Generating Dataset Using Multi-Core Architecture on Edge DeviceEnsembles of bidirectional LSTM and GRU neural nets for predicting mother-infant synchrony in videos.- Feature selection with L1 regularization  in formal neurons.- Graph-Based Fault Localization in Python Projects with Class-Imbalanced Learning.- HCER: Hierarchical Clustering-Ensemble Regressor.- Machine Learning Modeling in Industrial Processes for Visual AnalysisMachine Learning modeling to provide assistance to basketball coaches.- Understanding Users' Confidence in Spoken Queries for Conversational Search Systems.- Unsupervised Anomaly Detection Combining PCA and Neural Gases.- Machine Learning.- A new approach to learn spatio-spectral texture representation with randomized networks: Application to Brazilian plant species identification.- Application of Directional Vectors for Independent Subspaces in Bio-inspired NetworksAssessing the Impact of Preprocessing Pipelines on fMRI based Autism Spectrum Disorder Classification: ABIDE II resultsData-Driven Methods for Wi-Fi Anomaly DetectionDiscrete-Time Replicator Equations and The Price of Cognition on Parallel Neural Networks.- Evaluating forecast distributions in neural network HAR-type models for range-based volatility.- Machine Learning Classification of Water Conductivity raw values of "Faneromeni" Reservoir in Crete.- Machine Learning-Based Feature Mapping for Enhanced Understanding of the Housing MarketMachine Learning-Driven Improvements in HRV Artifact Correction for Psychosis Prediction in the Schizophrenia Spectrum.- Machine Unlearning; A Comparative AnalysisSecurity Analysis of Cryptographic Algorithms: Hints from Machine Learning.

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