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Intelligent Systems: 34th Brazilian Conference, BRACIS 2024, Belém do Parį, Brazil, November 1721, 2024, Proceedings, Part IV [Mīkstie vāki]

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  • Formāts: Paperback / softback, 270 pages, height x width: 235x155 mm, 60 Illustrations, color; 12 Illustrations, black and white; XVII, 270 p. 72 illus., 60 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Artificial Intelligence 15415
  • Izdošanas datums: 31-Jan-2025
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031790375
  • ISBN-13: 9783031790379
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  • Cena: 54,05 €*
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Intelligent Systems: 34th Brazilian Conference, BRACIS 2024, Belém do Pará, Brazil, November 1721, 2024, Proceedings, Part IVPalielināt
  • Formāts: Paperback / softback, 270 pages, height x width: 235x155 mm, 60 Illustrations, color; 12 Illustrations, black and white; XVII, 270 p. 72 illus., 60 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Artificial Intelligence 15415
  • Izdošanas datums: 31-Jan-2025
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031790375
  • ISBN-13: 9783031790379
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783031790379.html
Keywords:
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 Parį, Brazil, during November 1721, 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.
.- 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.