Marcelo Keese Albertini

According to our database, Marcelo Keese Albertini authored at least 35 papers between 2007 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Validation of the Hospital Score as Predictor of 30-Day Potentially Avoidable Readmissions in a Brazilian Population: Retrospective Cohort Study.

Nayara Cristina da Silva, Marcelo Keese Albertini, André Ricardo Backes, Geórgia das Graças Pena

J. Circuits Syst. Comput., June, 2023

Dynamic Compact Data Structure for Temporal Reachability with Unsorted Contact Insertions.

Luiz Fernando Afra Brito, Marcelo Keese Albertini, Bruno Augusto Nassif Travençolo, Gonzalo Navarro

CoRR, 2023

A Dynamic Data Structure for Representing Timed Transitive Closures on Disk.

Luiz F. Afra Brito, Marcelo Keese Albertini, Bruno A. N. Travençolo

CoRR, 2023

Prediction of readmissions in hospitalized children and adolescents by machine learning.

Nayara Cristina da Silva, Marcelo Keese Albertini, André Ricardo Backes, Geórgia das Graças Pena

Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023

2022

A dynamic data structure for temporal reachability with unsorted contact insertions.

Luiz F. A. Brito, Marcelo K. Albertini, Arnaud Casteigts, Bruno A. N. Travençolo

Soc. Netw. Anal. Min., 2022

Aerial image super-resolution based on deep recursive dense network for disaster area surveillance.

Feiqiang Liu, Qiang Yu, Lihui Chen, Gwanggil Jeon, Marcelo Keese Albertini, Xiaomin Yang

Pers. Ubiquitous Comput., 2022

Medical image super-resolution with laplacian dense network.

Rui Tang, Lihui Chen, Rongzhu Zhang, Awais Ahmad, Marcelo Keese Albertini, Xiaomin Yang

Multim. Tools Appl., 2022

Potential of sixth-generation technologies for emerging future wireless networks.

Gwanggil Jeon, Valerio Bellandi, Abdellah Chehri, Marcelo Keese Albertini

Trans. Emerg. Telecommun. Technol., 2022

A Review of In-Memory Space-Efficient Data Structures for Temporal Graphs.

Luiz F. A. Brito, Bruno A. N. Travençolo, Marcelo K. Albertini

CoRR, 2022

2021

LMSN: a lightweight multi-scale network for single image super-resolution.

Yiye Zou, Xiaomin Yang, Marcelo Keese Albertini, Farhan Hussain

Multim. Syst., 2021

Guest editorial: Special issue on design architecture and applications of smart embedded devices in internet of things.

Gwanggil Jeon, Awais Ahmad, Abdellah Chehri, Marcelo Keese Albertini

J. Syst. Archit., 2021

Lightweight network with one-shot aggregation for image super-resolution.

Rui Tang, Lihui Chen, Yiye Zou, Zhibing Lai, Marcelo Keese Albertini, Xiaomin Yang

J. Real Time Image Process., 2021

Image super-resolution via enhanced multi-scale residual network.

MengJie Wang, Xiaomin Yang, Marco Anisetti, Rongzhu Zhang, Marcelo Keese Albertini, Kai Liu

J. Parallel Distributed Comput., 2021

VisGraphNet: A complex network interpretation of convolutional neural features.

João Batista Florindo, Young-Sup Lee, Kyungkoo Jun, Gwanggil Jeon, Marcelo Keese Albertini

Inf. Sci., 2021

Practical evaluation of Lyndon factors via alphabet reordering.

Marcelo K. Albertini, Felipe A. Louza

CoRR, 2021

Wild boar recognition using convolutional neural networks.

Luís Carlos Silva Júnior, Maricéia B. S. Pàdua, Leonardo M. Ogusuku, Marcelo Keese Albertini, Renato Pimentel, André R. Backes

Concurr. Comput. Pract. Exp., 2021

2020

Multifocus image fusion using convolutional neural network.

Yu Wen, Xiaomin Yang, Turgay Çelik, Olga S. Sushkova, Marcelo Keese Albertini

Multim. Tools Appl., 2020

An empirical evaluation of random transformations applied to ensemble clustering.

Gabriel Damasceno Rodrigues, Marcelo Keese Albertini, Xiaomin Yang

Multim. Tools Appl., 2020

Entropy-Based Image Fusion with Joint Sparse Representation and Rolling Guidance Filter.

Yudan Liu, Xiaomin Yang, Rongzhu Zhang, Marcelo Keese Albertini, Turgay Çelik, Gwanggil Jeon

Entropy, 2020

Multi-Phases and Various Feature Extraction and Selection Methodology for Ensemble Gradient Boosting in Estimating Respiratory Rate.

Soojeong Lee, Chang-Hwan Son, Marcelo Keese Albertini, Henrique C. Fernandes

IEEE Access, 2020

Wild boar Classification by Using a Fusion of Texture Analysis Methods.

Luís C. S. Júnior, Maricéia B. S. Pàdua, Leonardo M. Ogusuku, Marcelo Keese Albertini, Renato Pimentel, André R. Backes

Proceedings of the 33rd SIBGRAPI Conference on Graphics, Patterns and Images, 2020

2018

Estimating data stream tendencies to adapt clustering parameters.

Marcelo Keese Albertini, Rodrigo Fernandes de Mello

Int. J. High Perform. Comput. Netw., 2018

2017

Visualization of Clusters in an Educational Data Set Based on Convex-Hull Shape Preservation Algorithm.

Marcelo Keese Albertini, André Ricardo Backes

Int. J. Pattern Recognit. Artif. Intell., 2017

Empirical evaluation of strategies to process range queries of numeric sequences in batch-mode.

Luiz F. A. Brito, Marcelo Keese Albertini

Proceedings of the XXXII Simpósio Brasileiro de Banco de Dados, 2017

Using Multiple Clustering Algorithms to Generate Constraint Rules and Create Consensus Clusters.

Gabriel Rodrigues da Silva, Marcelo Keese Albertini

Proceedings of the 2017 Brazilian Conference on Intelligent Systems, 2017

2016

Min-heap-based scheduling algorithm: an approximation algorithm for homogeneous and heterogeneous distributed systems.

Paulo Henrique Ribeiro Gabriel, Marcelo Keese Albertini, Antonio Castelo, Rodrigo Fernandes de Mello

Int. J. Parallel Emergent Distributed Syst., 2016

2015

MP-Draughts: Unsupervised Learning Multi-agent System Based on MLP and Adaptive Neural Networks.

Valquiria Aparecida Rosa Duarte, Rita Maria da Silva Julia, Marcelo Keese Albertini, Henrique Castro Neto

Proceedings of the 27th IEEE International Conference on Tools with Artificial Intelligence, 2015

2013

Data stream dynamic clustering supported by Markov chain isomorphisms.

Marcelo Keese Albertini, Rodrigo Fernandes de Mello

Intell. Data Anal., 2013

Energy-based function to evaluate data stream clustering.

Marcelo Keese Albertini, Rodrigo Fernandes de Mello

Adv. Data Anal. Classif., 2013

2012

Adapting the inductive bias of data-stream clustering algorithms.

Marcelo Keese Albertini

PhD thesis, 2012

2011

Entropy-Based Approach to Analyze and Classify Mineral Aggregates.

Lilian Tais de Gouveia, Luciano da Fontoura Costa, Luciano José Senger, Marcelo Keese Albertini, Rodrigo Fernandes de Mello

J. Comput. Civ. Eng., 2011

2010

Variation Detection applied in User Signature Verification.

Rodrigo Fernandes de Mello, Matheus L. dos Santos, Marcelo Keese Albertini

RITA, 2010

A Self-Organizing Neural Network to Approach Novelty Detection.

Marcelo Keese Albertini, Rodrigo Fernandes de Mello

Proceedings of the Intelligent Systems for Automated Learning and Adaptation: Emerging Trends and Applications, 2010

2008

A Novel Approach to Quantify Novelty Levels Applied on Ubiquitous Music Distribution.

Marcelo Keese Albertini, Kuan-Ching Li, Rodrigo Fernandes de Mello

Proceedings of the 3rd IEEE Asia-Pacific Services Computing Conference, 2008

2007

A self-organizing neural network for detecting novelties.

Marcelo Keese Albertini, Rodrigo Fernandes de Mello

Proceedings of the 2007 ACM Symposium on Applied Computing (SAC), 2007