Deep Learning Theory and Applications -

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Editeur : Springer International Publishing Ag

Langue : Anglais

Parution : 01/07/2023

Format : Moyen, de 350g à 1kg

Nombre de pages : 500

Expédition : 750

Dimensions : 23.5 x 15.5 x 2.7

ISBN : 303139058X

Résumé :
This book consitiutes the refereed proceedings of the 4th International Conference on Deep Learning Theory and Applications, DeLTA 2023, held in Rome, Italy from 13 to 14 July 2023.

The 9 full papers and 22 short papers presented were thoroughly reviewed and selected from the 42 qualified submissions. The scope of the conference includes such topics as models and algorithms; machine learning; big data analytics; computer vision applications; and natural language understanding.

Sommaire:
Pervasive AI: (deep) Learning into the Wild.- Deep Reinforcement Learning to Improve Traditional Supervised Learning Methodologies.- Synthetic Network Traffic Data Generation and Classification of Advanced Persistent Threat Samples: A Case Study with GANs and XGBoost.- Improving Primate Sounds Classification Using Binary Presorting for Deep Learning.- Towards Exploring Adversarial Learning for Anomaly Detection in Complex Driving Scenes.- Dynamic Prediction of Survival Status in Patients Undergoing Cardiac Catheterization Using a Joint Modeling Approach.- A Machine Learning Framework for Shuttlecock Tracking and Player Service Fault Detection.- An Automated Dual-Module Pipeline for Stock Prediction: Integrating N-Perception Period Power Strategy and NLP-Driven.- Sentiment Analysis for Enhanced Forecasting Accuracy and Investor Insight.- Machine Learning Applied to Speech Recordings for Parkinson?s Disease Recognition.- Vision Transformers for Galaxy Morphology Classification: Fine-Tuning Pre-Trained Networks vs. Training from Scratch.- A Study of Neural Collapse for Text Classification.- Research Data Reusability with Content-Based Recommender System.- MSDeepNet: A Novel Multi-Stream Deep Neural Network for Real-World Anomaly Detection in Surveillance Videos.- A Novel Probabilistic Approach for Detecting Concept Drift in Streaming Data.- Explaining Relation Classification Models with Semantic Extents.- Phoneme-Based Multi-Task Assessment of Affective Vocal Bursts.- Using Artificial Intelligence to Reduce the Risk of Transfusion Hemolytic Reactions.- ALE: A Simulation-Based Active Learning Evaluation Framework for the Parameter-Driven Comparison of Query Strategies for NLP.- Exploring ASR Models in Low-Resource Languages: Use-Case the Macedonian Language.- Facilitating Enterprise Model Classification via Embedding Symbolic Knowledge into Neural Network Models.- Explainable Abnormal Time Series Subsequence Detection Using Random Convolutional Kernels.- TaxoSBERT: Unsupervised Taxonomy Expansion Through Expressive Semantic Similarity.- Towards Equitable AI in HR: Designing a Fair, Reliable, and Transparent Human Resource Management Application.- An Explainable Approach for Early Parkinson Disease Detection Using Deep Learning.- UMLDesigner: An Automatic UML Diagram Design Tool.- Graph Neural Networks for Circuit Diagram Pattern Generation.- Generative Adversarial Networks for Domain Translation in Unpaired Breast DCE-MRI Datasets.- A Survey on Reinforcement Learning and Deep Reinforcement Learning for Recommender Systems.- GAN-Powered Model&Landmark-Free Reconstruction: A Versatile Approach for High-Quality 3D Facial and Object Recovery from Single Images.-GAN-Based LiDAR Intensity Simulation.- Evaluating Prototypes and Criticisms for Explaining Clustered Contributions in Digital Public Participation Processes.- FRLL-Beautified: A Dataset of Fun Selfie Filters with Facial Attributes.- CSR & Sentiment Analysis: A New Customized Dictionary.