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.

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. They deal with reinforcement; natural language; biomedical applications; classificaiton; deep learning; convolutional neural networks. .