Deep Learning Theory and Applications
Description
This book constitutes revised selected papers from the 6th International Conference on Deep Learning Theory and Applications, DeLTA 2025, which took place in Bilbao, Spain, during June 12-13, 2025.
The 9 full papers and 13 short papers presented in this volume were carefully reviewed and selected from 42 submissions. The conference is focusing on models and algorithms; machine learning; Big Data analytics; computer vision applications; and natural language understanding.
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Content
.- End-to-End ASR Model with Iterative Attention Mechanism Enhanced RNN Model for Phoneme Recognition.
.- Diagnostic Trouble Codes Prediction with DTC-GOAT and Ensembles.
.- A Fast Fourier Transform-Aided Diffusion-Based U-Net Architecture for Microscopic Medical Image Segmentation.
.- Non-Cooperative Game Theory-Aided Learning of CNN Models for Skin Lesion Classification.
.- LoRA-Based Summarization of Data Privacy Clauses in Terms and Conditions Documents Aligned with India's 2023 Digital Personal Data Protection Act.
.- Comparison of AI Speech-to-Text Systems and Their Application in Artillery Command and Fire Control Systems.
.- Rhythm Fusion: Synchronizing Audio and Motion Features for Music-Driven Dance Generation.
.- Leveraging Synthetic Data for Deep-Learning-Based Road Crack Segmentation from UAV Imagery.
.- Trojan Vulnerabilities in Host-Based Intrusion Detection Systems.
.- Identification of Key Feature Interactions via PDP Decomposition.
.- Variational Mode Decomposition (VMD) Parameter Selection Using Sine-Cosine Algorithm (SCA): Application on Vibration Signals for Rotating Machinery Monitoring.
.- Forecasting Ethereum Prices with Machine Learning, Deep Learning, and Explainable Artificial Intelligence Using Multi-Source Market Articles and Hybrid Sentiment Analysis.
.- Application of Neural Networks to Ultrasonic Data for Discrimination of Fat Types in Muscle Tissue Models.
.- SwiNight: Class Imbalanced Night-Time Accident Detection with Swin Transformer.
.- Enhancing Off-Policy Method SAC with KAN for Continuous Reinforcement Learning.
.- Context-Aware Deep Learning for Longitudinal Data Imputation in Parkinson's Disease.
.- Investigating Zero-Shot Diagnostic Pathology in Vision-Language Models with Efficient Prompt Design.
.- Achieving Zero False Negatives: Optimizing Anomaly Detection with Genetic Neural Architecture Search.
.- Whisper-Conformer: A Modified Automatic Speech Recognition for Thai Speech Recognition.
.- RevCD: Reversed Conditional Diffusion for Generalized Zero-Shot Learning.
.- Toward an Explainable Heatmap-Based Deep Neural Network for Product Defect Classification and Machine Failure Prediction in Industry 4.0.
.- Question Answering in a Low-Resource Language: Dataset and Deep Learning Adaptations for Sinhala.