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020 _a9783031390593
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024 7 _a10.1007/978-3-031-39059-3
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050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
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072 7 _aCOM004000
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082 0 4 _a006.3
_223
245 1 0 _aDeep Learning Theory and Applications
_h[electronic resource] :
_b4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023, Proceedings /
_cedited by Donatello Conte, Ana Fred, Oleg Gusikhin, Carlo Sansone.
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2023.
300 _aXVII, 482 p. 196 illus., 162 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aCommunications in Computer and Information Science,
_x1865-0937 ;
_v1875
505 0 _aPervasive 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 _aThis 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.
650 0 _aArtificial intelligence.
650 0 _aMachine learning.
650 0 _aApplication software.
650 0 _aData mining.
650 0 _aComputers.
650 0 _aNatural language processing (Computer science).
650 1 4 _aArtificial Intelligence.
650 2 4 _aMachine Learning.
650 2 4 _aComputer and Information Systems Applications.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aComputing Milieux.
650 2 4 _aNatural Language Processing (NLP).
700 1 _aConte, Donatello.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aFred, Ana.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aGusikhin, Oleg.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aSansone, Carlo.
_eeditor.
_4edt
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710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031390586
776 0 8 _iPrinted edition:
_z9783031390609
830 0 _aCommunications in Computer and Information Science,
_x1865-0937 ;
_v1875
856 4 0 _uhttps://doi.org/10.1007/978-3-031-39059-3
912 _aZDB-2-SCS
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