Deep Learning Theory and Applications 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023, Proceedings /
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 submission...
Đã lưu trong:
| Tác giả của công ty: | |
|---|---|
| Tác giả khác: | , , , |
| Định dạng: | Điện tử eBook |
| Ngôn ngữ: | Tiếng Anh |
| Được phát hành: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2023.
|
| Phiên bản: | 1st ed. 2023. |
| Loạt: | Communications in Computer and Information Science,
1875 |
| Những chủ đề: | |
| Truy cập trực tuyến: | https://doi.org/10.1007/978-3-031-39059-3 |
| Các nhãn: |
Thêm thẻ
Không có thẻ, Là người đầu tiên thẻ bản ghi này!
|
MARC
| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 001 | 978-3-031-39059-3 | ||
| 003 | DE-He213 | ||
| 005 | 20260810154627.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 230730s2023 sz | o |||| 0|eng d | ||
| 020 | |a 9783031390593 |9 978-3-031-39059-3 | ||
| 024 | 7 | |a 10.1007/978-3-031-39059-3 |2 doi | |
| 050 | 4 | |a Q334-342 | |
| 050 | 4 | |a TA347.A78 | |
| 072 | 7 | |a UYQ |2 bicssc | |
| 072 | 7 | |a COM004000 |2 bisacsh | |
| 072 | 7 | |a UYQ |2 thema | |
| 082 | 0 | 4 | |a 006.3 |2 23 |
| 245 | 1 | 0 | |a Deep Learning Theory and Applications |h [electronic resource] : |b 4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023, Proceedings / |c edited by Donatello Conte, Ana Fred, Oleg Gusikhin, Carlo Sansone. |
| 250 | |a 1st ed. 2023. | ||
| 264 | 1 | |a Cham : |b Springer Nature Switzerland : |b Imprint: Springer, |c 2023. | |
| 300 | |a 1 online resource (XVII, 482 p. 196 illus.). |b 162 illus. in color. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Communications in Computer and Information Science, |x 1865-0937 ; |v 1875 | |
| 505 | 0 | |a 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. | |
| 520 | |a 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. | ||
| 588 | |a Print version record. | ||
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Application software. | |
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Computers. | |
| 650 | 0 | |a Natural language processing (Computer science). | |
| 650 | 1 | 4 | |a Artificial Intelligence. |
| 650 | 2 | 4 | |a Machine Learning. |
| 650 | 2 | 4 | |a Computer and Information Systems Applications. |
| 650 | 2 | 4 | |a Data Mining and Knowledge Discovery. |
| 650 | 2 | 4 | |a Computing Milieux. |
| 650 | 2 | 4 | |a Natural Language Processing (NLP). |
| 700 | 1 | |a Conte, Donatello. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Fred, Ana. |e editor. |0 (orcid)0000-0003-1320-5024 |1 https://orcid.org/0000-0003-1320-5024 |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Gusikhin, Oleg. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Sansone, Carlo. |e editor. |0 (orcid)0000-0002-8176-6950 |1 https://orcid.org/0000-0002-8176-6950 |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783031390586 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031390609 |
| 830 | 0 | |a Communications in Computer and Information Science, |x 1865-0937 ; |v 1875 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-031-39059-3 |
| 912 | |a ZDB-2-SCS | ||
| 912 | |a ZDB-2-SXCS | ||
| 912 | |a ZDB-2-SXPS | ||
| 950 | |a Computer Science (SpringerNature-11645) | ||
| 950 | |a Computer Science (R0) (SpringerNature-43710) | ||
| 950 | |a Springer Nature Proceedings Computer Science (SpringerNature-85344) | ||