Intelligent Systems

34th Brazilian Conference, BRACIS 2024, Belém do Pará, Brazil, November 17–21, 2024, Proceedings, Part IV

Häftad, Engelska, 2025

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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.

Produktinformation

Utgivningsdatum2025-01-31
Mått155 x 235 x 16 mm
Vikt441 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor270
FörlagSpringer International Publishing AG
ISBN9783031790379
OriginaltitelIntelligent Systems

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.- 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.