A self-organizing neural network for detecting novelties. - Marcelo Keese Albertini; Rodrigo Fernandes de Mello (SAC, 2007)

A Novel Approach to Quantify Novelty Levels Applied on Ubiquitous Music Distribution. - Marcelo Keese Albertini; Kuan-Ching Li; Rodrigo Fernandes de Mello (APSCC, 2008)

A Self-Organizing Neural Network to Approach Novelty Detection. - Marcelo Keese Albertini; Rodrigo Fernandes de Mello (Intelligent Systems for Automated Learning and Adaptation, 2010)

Variation Detection applied in User Signature Verification. - Rodrigo Fernandes de Mello; Matheus L. dos Santos; Marcelo Keese Albertini (RITA, 2010)

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)

Adapting the inductive bias of data-stream clustering algorithms. - Marcelo Keese Albertini (2012)

Energy-based function to evaluate data stream clustering. - Marcelo Keese Albertini; Rodrigo Fernandes de Mello (Adv. Data Anal. Classif., 2013)

Data stream dynamic clustering supported by Markov chain isomorphisms. - Marcelo Keese Albertini; Rodrigo Fernandes de Mello (Intell. Data Anal., 2013)

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 (ICTAI, 2015)

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)

Using Multiple Clustering Algorithms to Generate Constraint Rules and Create Consensus Clusters. - Gabriel Rodrigues da Silva; Marcelo Keese Albertini (BRACIS, 2017)

Empirical evaluation of strategies to process range queries of numeric sequences in batch-mode. - Luiz F. A. Brito; Marcelo Keese Albertini (SBBD (Short Papers), 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)

Estimating data stream tendencies to adapt clustering parameters. - Marcelo Keese Albertini; Rodrigo Fernandes de Mello (Int. J. High Perform. Comput. Netw., 2018)

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 (SIBGRAPI, 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)

Entropy-Based Image Fusion with Joint Sparse Representation and Rolling Guidance Filter. - Yudan Liu; Xiaomin Yang; Rongzhu Zhang; Marcelo Keese Albertini; Turgay Çelik 001; Gwanggil Jeon (Entropy, 2020)

An empirical evaluation of random transformations applied to ensemble clustering. - Gabriel Damasceno Rodrigues; Marcelo Keese Albertini; Xiaomin Yang (Multim. Tools Appl., 2020)

Multifocus image fusion using convolutional neural network. - Yu Wen; Xiaomin Yang; Turgay Çelik 001; Olga S. Sushkova; Marcelo Keese Albertini (Multim. Tools Appl., 2020)

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)

Practical evaluation of Lyndon factors via alphabet reordering. - Marcelo K. Albertini; Felipe A. Louza (CoRR, 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)

Image super-resolution via enhanced multi-scale residual network. - Mengjie Wang; Xiaomin Yang; Marco Anisetti; Rongzhu Zhang; Marcelo Keese Albertini; Kai Liu 012 (J. Parallel Distributed Comput., 2021)

Lightweight network with one-shot aggregation for image super-resolution. - Rui Tang; Lihui Chen 002; Yiye Zou; Zhibing Lai; Marcelo Keese Albertini; Xiaomin Yang (J. Real Time Image Process., 2021)

Guest editorial: Special issue on design architecture and applications of smart embedded devices in internet of things. - Gwanggil Jeon; Awais Ahmad 001; Abdellah Chehri; Marcelo Keese Albertini (J. Syst. Archit., 2021)

LMSN: a lightweight multi-scale network for single image super-resolution. - Yiye Zou; Xiaomin Yang; Marcelo Keese Albertini; Farhan Hussain (Multim. Syst., 2021)

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)

Potential of sixth-generation technologies for emerging future wireless networks. - Gwanggil Jeon; Valerio Bellandi; Abdellah Chehri; Marcelo Keese Albertini (Trans. Emerg. Telecommun. Technol., 2022)

Medical image super-resolution with laplacian dense network. - Rui Tang; Lihui Chen 002; Rongzhu Zhang; Awais Ahmad 001; Marcelo Keese Albertini; Xiaomin Yang (Multim. Tools Appl., 2022)

Aerial image super-resolution based on deep recursive dense network for disaster area surveillance. - Feiqiang Liu; Qiang Yu; Lihui Chen 002; Gwanggil Jeon; Marcelo Keese Albertini; Xiaomin Yang (Pers. Ubiquitous Comput., 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)

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 (SAC, 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)

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., 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 001 (Comput. J., 2024)

Machine learning for hospital readmission prediction in pediatric population. - Nayara Cristina da Silva; Marcelo Keese Albertini; André Ricardo Backes; Geórgia das Graças Pena (Comput. Methods Programs Biomed., 2024)

Productivity profile of CNPq scholarship researchers in computer science from 2017 to 2021. - Marcelo Keese Albertini; André Ricardo Backes (CoRR, 2024)

Guest Editorial: Special Issue on Dark Side of the Socio-Cyber World: Media Manipulation, Fake News, and Misinformation. - Gwanggil Jeon; Xiaochun Cheng; Abdellah Chehri; Giancarlo Fortino; Marcelo K. Albertini; Shiping Wen 001 (IEEE Trans. Comput. Soc. Syst., 2024)

Beyond the Black-Box: Understanding XGBoost to Predict Pediatric Hospital Readmission. - Nayara Cristina da Silva; Marcelo Keese Albertini; André Ricardo Backes; Geórgia das Graças Pena (CBMS, 2025)