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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
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
Autore Conte Donatello
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (496 pages)
Disciplina 006.3
Altri autori (Persone) FredAna
GusikhinOleg
SansoneCarlo
Collana Communications in Computer and Information Science
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)
ISBN 3-031-39059-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
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.
Record Nr. UNISA-996547971403316
Conte Donatello  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Deep Learning Theory and Applications : 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023, Proceedings / / edited by Donatello Conte, Ana Fred, Oleg Gusikhin, Carlo Sansone
Deep Learning Theory and Applications : 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023, Proceedings / / edited by Donatello Conte, Ana Fred, Oleg Gusikhin, Carlo Sansone
Autore Conte Donatello
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (496 pages)
Disciplina 006.3
006.31
Altri autori (Persone) FredAna
GusikhinOleg
SansoneCarlo
Collana Communications in Computer and Information Science
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)
ISBN 3-031-39059-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
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.
Record Nr. UNINA-9910736017403321
Conte Donatello  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui