Pan-African Conference on Artificial Intelligence

Second Conference, PanAfriCon AI 2023, Addis Ababa, Ethiopia, October 5-6, 2023, Revised Selected Papers, Part I
2024
ISBN: 978-3-031-57623-2
Verlag: Springer Nature Switzerland

Buch, Englisch, Band 2068, 282 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 458 g

Reihe: Communications in Computer and Information Science

This two-volume set, CCIS 2068 and 2069, constitutes selected papers presented during the Second Pan-African Conference on Artificial Intelligence, PanAfriCon AI 2023, held in Addis Ababa, Ethiopia, in October 2023. The set goal of the conference is to exchange the best practices of joint Pan-African efforts to provide solutions for Africa’s key 21st century challenges in the social, economic and ecologic domains.

The 29 papers were thoroughly reviewed and selected from 134 submissions.

The papers are organized in the following topical sections: Medical AI; Natural Language Processing, Text and Speech Processing; AI in Finance and Cyber Security; Autonomous Vehicles; AI Ethics and Life Sciences.

Zielgruppe

Research

Autoren/Hrsg.

Debelee, Taye Girma

Megersa Ayano, Yehualashet

Ibenthal, Achim

Schwenker, Friedhelm

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Spracherkennung, Sprachverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
• Mathematik | Informatik EDV | Informatik Angewandte Informatik

Inhaltsverzeichnis

Machine learning based stroke segmentation and classification from CT-Scan: A survey.- Multitask Deep Convolutional Neural Network with Attention for Pulmonary Tuberculosis Detection and Weak Localization of Pathological Manifestations in Chest X-ray.- Automated Kidney Segmentation and Disease Classification Using CNN-based Models.- Generating Synthetic Brain Tumor Data using StyleGAN3 For Lower Class Enhancement.- Optimized Machine Learning models for hepatitis C prediction: Leveraging Optuna for Hyperparameter Tuning and Streamlit for Model deployment.- Explainable Rhythm-based Heart Disease Detection from ECG Signals.- Development of an Explainable Heart Failure Patients Survival Status Prediction Model Using Machine Learning Algorithms.- Natural Language Processing, Text and Speech Processing.- Transfer of models and resources for under-resourced languages Semantic Role Labeling.- Speaker Identification under Noisy Conditions using Hybrid Deep Learning Model.- State-of-the-Art Approaches to Word Sense Disambiguation: A Multilingual Investigation.- Ge’ez Syntax Error Detection Using Deep Learning Approaches.- Tigrinya End-to-End Speech Recognition: A Hybrid Connectionist Temporal Classification-Attention Approach.- DNN-based Supervised Spontaneous Court Hearing Transcription for Amharic.- Typewritten OCR Model for Ethiopic Characters.- Compressed Amharic Text: A Prediction by Partial Match Context-modeling Algorithm.- AI in Finance and Cyber Security.- Improving the Accuracy of Financial Bankruptcy Prediction using Ensemble Learning Techniques.- Deep Learning and Machine Learning Techniques for Credit Scoring: A Review.- MoMTSim Platform.- An Investigation and Analysis of Vulnerabilities Surrounding Cryptocurrencies and Blockchain Technology.- Towards a Supervised Machine Learning Algorithm for Cyberattacks Detectionand Prevention in a Smart Grid Cybersecurity System.- Classification of DGA-Based Malware Using Deep Hybrid Learning.- A Review and Analysis of Cybersecurity Threats and Vulnerabilities, by Development of a Fuzzy Rule-Based Expert System.- Autonomous Vehicles.- Neural Network Based Model Reference Adaptive Control of Quadrotor UAV for Precision Agriculture.- AI Ethics and Life Sciences.- Systems Thinking Application to Ethical and Privacy Considerations in AI-Enabled Syndromic Surveillance Systems: Requirements for Under-Resourced Countries in Southern Africa.- Fake vs. Real Face Discrimination Using Convolutional Neural Networks.- Hybrid of Ensemble Machine Learning and Nature-Inspired Algorithms.