Atnaujinkite slapukų nuostatas

El. knyga: Intelligent Systems: 34th Brazilian Conference, BRACIS 2024, Belem do Para, Brazil, November 17-21, 2024, Proceedings, Part II

Edited by , Edited by
Kitos knygos pagal šią temą:
Intelligent Systems: 34th Brazilian Conference, BRACIS 2024, Belem do Para, Brazil, November 17-21, 2024, Proceedings, Part IIDidesnis paveikslėlis

DRM apribojimai

  • Kopijuoti:

    neleidžiama

  • Spausdinti:

    neleidžiama

  • El. knygos naudojimas:

    Skaitmeninių teisių valdymas (DRM)
    Leidykla pateikė šią knygą šifruota forma, o tai reiškia, kad norint ją atrakinti ir perskaityti reikia įdiegti nemokamą programinę įrangą. Norint skaityti šią el. knygą, turite susikurti Adobe ID . Daugiau informacijos  čia. El. knygą galima atsisiųsti į 6 įrenginius (vienas vartotojas su tuo pačiu Adobe ID).

    Reikalinga programinė įranga
    Norint skaityti šią el. knygą mobiliajame įrenginyje (telefone ar planšetiniame kompiuteryje), turite įdiegti šią nemokamą programėlę: PocketBook Reader (iOS / Android)

    Norint skaityti šią el. knygą asmeniniame arba „Mac“ kompiuteryje, Jums reikalinga  Adobe Digital Editions “ (tai nemokama programa, specialiai sukurta el. knygoms. Tai nėra tas pats, kas „Adobe Reader“, kurią tikriausiai jau turite savo kompiuteryje.)

    Negalite skaityti šios el. knygos naudodami „Amazon Kindle“.

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.
.- Main Track.

.- Going Bananas! - Unfolding Program Synthesis with Origami.

.- GovBERT-BR: A BERT-based Language Model for Brazilian Portuguese
Governmental Data.

.- Growing Self-Organizing Maps for Multi-Label Classification.

.- HEACT: Hybrid Evolutionary Algorithm for the Multi-region Multi-objective
Cloud Task Scheduling Problem. A Study of Workflow Scheduling in AWS EC2.

.- Heuristic Solutions for the 2D Bin-Packing Problem with Varied Size.

.- Humanities and AI: ethical education in technology careers.

.- Impact of parent selection operator on the FDEA algorithm.

.- Improving LLMs Reasoning and Planning with Finite-State Machines.

.- Improving Short-content Misinformation Detection using Multiple Aspect
Trajectories Classification Techniques.

.- InRanker: Distilled Rankers for Zero-shot Information Retrieval.

.- Investigating Behavior Cloning from Few Demonstrations for Autonomous
Driving based on Birds-Eye View in Simulated Cities.

.- Investigating Universal Adversarial Attacks Against Transformers-based
Automatic Essay Scoring Systems.

.- Likelihood Estimator for Multi Model-Based Reinforcement Learning.

.- LLM-Driven Chest X-Ray Report Generation With a Modular and Reduced-Size
Architecture.

.- Multilingual Extractive Summarization: Investigating State-of-the-Art
Methods for Brazilian Portuguese and Other Languages.

.- Multimodal and Hybrid Models for predicting SCD Risk in Chagas
Cardiomyopathy.

.- On the Equivalence between Logic Programs and Bipolar Argumentation
Frameworks.

.- Optimizing CleanUNet Architecture Parameters for Enhancing Speech
Denoising.

.- Portuguese emotion detection model using BERTimbau applied to COVID-19
news and replies.

.- Predicting Bull and Bear Markets: A Deep Learning and Linear Regression
Study in Cryptocurrencies.

.- Predicting Energy Consumption Data Using Deep Learning: An LSTM Approach.

.- Pseudonymization in Legal Texts according to the LGPD: A Named Entity
Recognition Approach.

.- ptt5-v2: A Closer Look at Continued Pretraining of T5 Models for the
Portuguese Language.

.- Question Answering with Texts and Tables through Deep Reinforcement
Learning.

.- Reinforcement Learning with Utility-Based Semantic for Goals.

.- SARA - A Generative AI for Legal Process Summarization Based on Chain of
Density Prompt Engineering.

.- Semi-Supervised Predictive Clustering Trees for Multi-Label Protein
Subcellular Localization.

.- Siamese Network-Based Prioritization for Enhanced Multi-Document
Summarization.

.- Standing on the shoulders of giants.

.- SurveySum: A Dataset for Summarizing Multiple Scientific Articles into a
Survey Section.

.- Traffic Forecasting using Federated Randomized High-order Fuzzy Cognitive
Maps.

.- Unsupervised Statistical Keyword Extraction Pipeline: Is LLM All You
Need?.

.- Using Complex Networks to Improve Legal Text Hierarchical Classification.
Daugiau apie elektronines knygas Daugiau apie elektronines knygas
Pastovi nuoroda: https://www.kriso.lt/db/97830317903242e.html