Vai al contenuto principale della pagina
Autore: |
Conte Donatello
![]() |
Titolo: |
Deep Learning Theory and Applications [[electronic resource] ] : 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023, Proceedings / / edited by Donatello Conte, Ana Fred, Oleg Gusikhin, Carlo Sansone
![]() |
Pubblicazione: | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
Edizione: | 1st ed. 2023. |
Descrizione fisica: | 1 online resource (496 pages) |
Disciplina: | 006.3 |
Soggetto topico: | Artificial intelligence |
Machine learning | |
Application software | |
Data mining | |
Computers | |
Natural language processing (Computer science) | |
Artificial Intelligence | |
Machine Learning | |
Computer and Information Systems Applications | |
Data Mining and Knowledge Discovery | |
Computing Milieux | |
Natural Language Processing (NLP) | |
Altri autori: |
FredAna
![]() ![]() ![]() |
Nota di contenuto: | 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. |
Sommario/riassunto: | 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. |
Titolo autorizzato: | Deep Learning Theory and Applications ![]() |
ISBN: | 3-031-39059-8 |
Formato: | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 996547971403316 |
Lo trovi qui: | Univ. di Salerno |
Opac: | Controlla la disponibilità qui |