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Deep Learning Theory and Applications

4th International Conference, DeLTA 2023, Rome, Italy, July 13–14, 2023, Proceedings

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Donatello Conte

    1. Université de Tours, Tours, France

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  2. Ana Fred

    1. Instituto de Telecomunicações and University of Lisbon, Lisbon, Portugal

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  3. Oleg Gusikhin

    1. Ford Motor Company, Commerce Township, USA

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  4. Carlo Sansone

    1. University of Naples Federico II, Naples, Italy

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Part of the book series: Communications in Computer and Information Science (CCIS, volume 1875)

Included in the following conference series:

Conference proceedings info: DeLTA 2023.

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Table of contents (31 papers)

  1. Front Matter

    Pages i-xvii
    Download chapter PDF

  2. Synthetic Network Traffic Data Generation and Classification of Advanced Persistent Threat Samples: A Case Study with GANs and XGBoost

    • T. J. Anande, M. S. Leeson
    Pages 1-18

  3. Improving Primate Sounds Classification Using Binary Presorting for Deep Learning

    • Michael Kölle, Steffen Illium, Maximilian Zorn, Jonas Nüßlein, Patrick Suchostawski, Claudia Linnhoff-Popien
    Pages 19-34

  4. Towards Exploring Adversarial Learning for Anomaly Detection in Complex Driving Scenes

    • Nour Habib, Yunsu Cho, Abhishek Buragohain, Andreas Rausch
    Pages 35-55

  5. Dynamic Prediction of Survival Status in Patients Undergoing Cardiac Catheterization Using a Joint Modeling Approach

    • Derun Xia, Yi-An Ko, Shivang Desai, Arshed A. Quyyumi
    Pages 56-70

  6. A Machine Learning Framework for Shuttlecock Tracking and Player Service Fault Detection

    • Akshay Menon, Abubakr Siddig, Cristina Hava Muntean, Pramod Pathak, Musfira Jilani, Paul Stynes
    Pages 71-83

  7. 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

    • Siddhant Singh, Archit Thanikella
    Pages 84-100

  8. Machine Learning Applied to Speech Recordings for Parkinson’s Disease Recognition

    • Lerina Aversano, Mario L. Bernardi, Marta Cimitile, Martina Iammarino, Antonella Madau, Chiara Verdone
    Pages 101-114

  9. Vision Transformers for Galaxy Morphology Classification: Fine-Tuning Pre-trained Networks vs. Training from Scratch

    • Rahul Kumar, Md Kamruzzaman Sarker, Sheikh Rabiul Islam
    Pages 115-125

  10. A Study of Neural Collapse for Text Classification

    • Jia Hui Feng, Edmund M.-K. Lai, Weihua Li
    Pages 126-142

  11. Research Data Reusability with Content-Based Recommender System

    • M. Amin Yazdi, Marius Politze, Benedikt Heinrichs
    Pages 143-156

  12. MSDeepNet: A Novel Multi-stream Deep Neural Network for Real-World Anomaly Detection in Surveillance Videos

    • Prabhu Prasad Dev, Pranesh Das, Raju Hazari
    Pages 157-172

  13. A Novel Probabilistic Approach for Detecting Concept Drift in Streaming Data

    • Sirvan Parasteh, Samira Sadaoui
    Pages 173-188

  14. Explaining Relation Classification Models with Semantic Extents

    • Lars Klöser, Andre Büsgen, Philipp Kohl, Bodo Kraft, Albert Zündorf
    Pages 189-208

  15. Phoneme-Based Multi-task Assessment of Affective Vocal Bursts

    • Tobias Hallmen, Silvan Mertes, Dominik Schiller, Florian Lingenfelser, Elisabeth André
    Pages 209-222

  16. Using Artificial Intelligence to Reduce the Risk of Transfusion Hemolytic Reactions

    • Maya Trutschl, Urska Cvek, Marjan Trutschl
    Pages 223-234

  17. ALE: A Simulation-Based Active Learning Evaluation Framework for the Parameter-Driven Comparison of Query Strategies for NLP

    • Philipp Kohl, Nils Freyer, Yoka Krämer, Henri Werth, Steffen Wolf, Bodo Kraft et al.
    Pages 235-253

  18. Exploring ASR Models in Low-Resource Languages: Use-Case the Macedonian Language

    • Konstantin Bogdanoski, Kostadin Mishev, Monika Simjanoska, Dimitar Trajanov
    Pages 254-268

  19. Facilitating Enterprise Model Classification via Embedding Symbolic Knowledge into Neural Network Models

    • Alexander Smirnov, Nikolay Shilov, Andrew Ponomarev
    Pages 269-279

  20. Explainable Abnormal Time Series Subsequence Detection Using Random Convolutional Kernels

    • Abdallah Amine Melakhsou, Mireille Batton-Hubert
    Pages 280-294
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  1. Deep Learning Theory and Applications

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About this book

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.

Editors and Affiliations

  • Université de Tours, Tours, France

    Donatello Conte

  • Instituto de Telecomunicações and University of Lisbon, Lisbon, Portugal

    Ana Fred

  • Ford Motor Company, Commerce Township, USA

    Oleg Gusikhin

  • University of Naples Federico II, Naples, Italy

    Carlo Sansone

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