Intelligent Systems : 12th Brazilian Conference, BRACIS 2023, Belo Horizonte, Brazil, September 25–29, 2023, Proceedings, Part II / edited by Murilo C. Naldi, Reinaldo A. C. Bianchi.

Format:

Book

Author/Creator:

Naldi, Murilo C.

Contributor:

Bianchi, Reinaldo A. C.

Series:

Lecture Notes in Artificial Intelligence, 2945-9141 ; 14196

Language:

English

Subjects (All):

Artificial intelligence.

Computer networks.

Data mining.

Education--Data processing.

Education.

Social sciences--Data processing.

Social sciences.

Artificial Intelligence.

Computer Communication Networks.

Data Mining and Knowledge Discovery.

Computers and Education.

Computer Application in Social and Behavioral Sciences.

Local Subjects:

Artificial Intelligence.

Computer Communication Networks.

Data Mining and Knowledge Discovery.

Computers and Education.

Computer Application in Social and Behavioral Sciences.

Physical Description:

1 online resource (443 pages)

Edition:

1st ed. 2023.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2023.

Summary:

The three-volume set LNAI 14195, 14196, and 14197 constitutes the refereed proceedings of the 12th Brazilian Conference on Intelligent Systems, BRACIS 2023, which took place in Belo Horizonte, Brazil, in September 2023. The 90 full papers included in the proceedings were carefully reviewed and selected from 242 submissions. They have been organized in topical sections as follows: Part I: Best papers; resource allocation and planning; rules and feature extraction; AI and education; agent systems; explainability; AI models; Part II: Transformer applications; convolutional neural networks; deep learning applications; reinforcement learning and GAN; classification; machine learning analysis; Part III: Evolutionary algorithms; optimization strategies; computer vision; language and models; graph neural networks; pattern recognition; AI applications. .

Contents:

Transformer Model for Fault Detection From Brazilian Pre-Salt Seismic Data

Evaluating Recent Legal Rhetorical Role Labeling Approaches Supported by Transformer Encoders

Dog Face Recognition Using Vision Transformer

Convolutional neural networks for the molecular detection of Covid-19

Hierarchical Graph Convolutional Networks for Image Classification

Interpreting Convolutional Neural Networks for Brain Tumor Classification: An Explainable Artificial Intelligence Approach

Enhancing Stock Market Predictions through the Integration of Convolutional and Recursive LSTM Blocks: A Cross-Market Analysis

Ensemble architectures and efficient fusion techniques for Convolutional Neural Networks: an analysis on resource optimization strategies

Dog Face Recognition using Deep Feature Embeddings

Clinical oncology textual notes analysis using machine learning and deep learning

EfficientDeepLab For Automated Trachea Segmentation On Medical Images

Multi-Label Classification of Pathologies in Chest Radiograph Images Using DenseNet

Does pre-training on brain-related tasks results in better deep-learning-based brain age biomarkers

Applying Reinforcement Learning for Multiple Functions in Swarm Intelligence

Deep Reinforcement Learning for Voltage Control in Power Systems

Performance Analysis of Generative Adversarial Networks and Diffusion Models for Face Aging

Occluded Face In-painting Using Generative Adversarial Networks - A Review Classification of facial images to assist in the diagnosis of Autism Spectrum Disorder: a study on the effect of face detection and landmark identification algorithms

Constructive Machine Learning and Hierarchical Multi-label Classification for Molecules Design

AutoMMLC: An Automated and Multi-objective Method for Multi-label Classification

Merging Traditional Feature Extraction and Deep Learning for Enhanced Hop Variety Classification: A Comparative Study Using the UFOP-HVD Dataset

Feature Selection and Hyperparameter Fine-tuning in Artificial Neural Networks for Wood Quality Classification

A Feature-based Out-of-Distribution Detection Approach in Skin Lesion Classification

A framework for characterizing what makes an instance hard to classify

Physicochemical Properties for Promoter Classification

Critical analysis of AI indicators in terms of weighting and aggregation approaches

Estimating Code Running Time Complexity with Machine Learning The Effect of Statistical Hypothesis Testing on Machine Learning Model Selection.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9783031453892

3031453891

OCLC:

1402816402