Buch, Englisch, 270 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 441 g
34th Brazilian Conference, BRACIS 2024, Belém do Pará, Brazil, November 17-21, 2024, Proceedings, Part IV
Buch, Englisch, 270 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 441 g
Reihe: Lecture Notes in Computer Science
ISBN: 978-3-031-79037-9
Verlag: Springer Nature Switzerland
The four-volume set LNAI 15412-15415 constitutes the refereed proceedings of the 34th Brazilian Conference on Intelligent Systems, BRACIS 2024, held in Belém do Pará, Brazil, during November 17–21, 2024.
The 116 full papers presented here were carefully reviewed and selected from 285 submissions. They were organized in three key tracks: 70 articles in the main track, showcasing cutting-edge AI methods and solid results; 10 articles in the AI for Social Good track, featuring innovative applications of AI for societal benefit using established methodologies; and 36 articles in other AI applications, presenting novel applications using established AI methods, naturally considering the ethical aspects of the application.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Technische Informatik Netzwerk-Hardware
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Geistes- und Sozialwissenschaften
- Sozialwissenschaften Pädagogik Lehrerausbildung, Unterricht & Didaktik E-Learning, Bildungstechnologie
Weitere Infos & Material
.- Best Papers.
.- A Topology-inspired approach to AGM Belief Change.
.- A Transformer-based Tabular Approach to Detect Toxic Comments.
.- Automatic Text Simplification for the Legal Domain in Brazilian Portuguese.
.- Developing Resource-Efficient Clinical LLMs for Brazilian Portuguese.
.- One-Class Learning for Data Stream through Graph Neural Networks.
.- Semi-Periodic Activation for Time Series Classification.
.- AI Applications for Social Good.
.-Automated and Intelligent Vocational Guidance System for Classifying Specialties Based on POSCOMP Microdata.
.- Classifying potentially non-compliant Portuguese language sentences concerning privacy policies.
.- Diversity in Data for Speech Processing in Brazilian Portuguese.
.- Elevating Healthcare AI: Achieving Efficiency and Accuracy in Medical Applications with Surrogate-Based Multiobjective Compression of ResNet50 CNNs.
.- Explainability of Machine Learning Models with XGBoost and SHAP values in the Context of Coping with Disasters.
.- Exploring Climatic Shifts in Brazilian Climates: Insights from ARMAX and Decision Trees and and Artificial Neural Networks.
.- Gender-Neutral English to Portuguese Machine Translator: Promoting Inclusive Language.
.- Hybrid Artificial Intelligence Model for Detecting Signs of Delayed Child Development.
.- Low birth weight in Brazil vulnerable groups: an analysis based on data mining and big data.
.- Modeling EEG data into graphs for the Prognostic of Patients in Coma using Graph Neural Networks.
.- Tackling Low-Resource ECG Classification with Self-Supervised Learning.
.- Tuning Hypothesis Creation: Combining Discrete and Continuous Spaces for Zero-Shot Hate Speech Detection.
