Rodrigo C. Barros

Orcid: 0000-0002-0782-9482

According to our database1, Rodrigo C. Barros authored at least 110 papers between 2008 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Unlocking The Potential Of Vision-Language Models For Mammography Analysis.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

One Against Many: Exploring Multi-task Learning Generalization in Source-Code Tasks.
Proceedings of the International Joint Conference on Neural Networks, 2024

An Experimental Analysis on Automated Machine Learning for Software Defect Prediction.
Proceedings of the IEEE Congress on Evolutionary Computation, 2024

LERMO: A Novel Web Game for AI-Enhanced Sign Language Recognition.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
A survey of evolutionary algorithms for supervised ensemble learning.
Knowl. Eng. Rev., 2023

Self-Supervised Adversarial Imitation Learning.
Proceedings of the International Joint Conference on Neural Networks, 2023

Radiomics for Predicting Oxygen Necessity in COVID-19 Patients Using Longitudinal Lung Computed Tomography.
Proceedings of the 23rd IEEE International Conference on Bioinformatics and Bioengineering, 2023

Zero-Shot Performance of the Segment Anything Model (SAM) in 2D Medical Imaging: A Comprehensive Evaluation and Practical Guidelines.
Proceedings of the 23rd IEEE International Conference on Bioinformatics and Bioengineering, 2023

2022
Debiasing Methods for Fairer Neural Models in Vision and Language Research: A Survey.
CoRR, 2022

Efficient Counterfactual Debiasing for Visual Question Answering.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

COBE: A Natural Language Code Search Robustness Benchmark.
Proceedings of the International Joint Conference on Neural Networks, 2022

How Resilient Are Imitation Learning Methods to Sub-optimal Experts?
Proceedings of the Intelligent Systems - 11th Brazilian Conference, 2022

Leveraging Textual Descriptions for House Price Valuation.
Proceedings of the Intelligent Systems - 11th Brazilian Conference, 2022

2021
Explainable Machine Learning for COVID-19 Pneumonia Classification With Texture-Based Features Extraction in Chest Radiography.
Frontiers Digit. Health, 2021

An extensive experimental evaluation of automated machine learning methods for recommending classification algorithms.
Evol. Intell., 2021

Model Compression in Object Detection.
Proceedings of the International Joint Conference on Neural Networks, 2021

2020
An Extensive Experimental Evaluation of Automated Machine Learning Methods for Recommending Classification Algorithms (Extended Version).
CoRR, 2020

HAPRec: Hybrid Activity and Plan Recognizer.
CoRR, 2020

Semi-supervised Classification of Chest Radiographs.
Proceedings of the Interpretable and Annotation-Efficient Learning for Medical Image Computing, 2020

Can We Trust Deep Learning Based Diagnosis? The Impact of Domain Shift in Chest Radiograph Classification.
Proceedings of the Thoracic Image Analysis - Second International Workshop, 2020

How Does Computer Animation Affect Our Perception of Emotions in Video Summarization?
Proceedings of the Advances in Visual Computing - 15th International Symposium, 2020

Attention-based 3D Object Reconstruction from a Single Image.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Augmented Behavioral Cloning from Observation.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Component Analysis for Visual Question Answering Architectures.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

An Evolutionary Algorithm for Learning Interpretable Ensembles of Classifiers.
Proceedings of the Intelligent Systems - 9th Brazilian Conference, 2020

Imitating Unknown Policies via Exploration.
Proceedings of the 31st British Machine Vision Conference 2020, 2020

A Novel Approach to Differentiate COVID-19 Pneumonia in Chest X-ray.
Proceedings of the 20th IEEE International Conference on Bioinformatics and Bioengineering, 2020

Adaptive Cross-Modal Embeddings for Image-Text Alignment.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
CrowdEst: a method for estimating (and not simulating) crowd evacuation parameters in generic environments.
Vis. Comput., 2019

Unsupervised domain adaptation for medical imaging segmentation with self-ensembling.
NeuroImage, 2019

Can we trust deep learning models diagnosis? The impact of domain shift in chest radiograph classification.
CoRR, 2019

Classifying Norm Conflicts using Learned Semantic Representations.
CoRR, 2019

Inducing Hierarchical Multi-label Classification rules with Genetic Algorithms.
Appl. Soft Comput., 2019

Fast and Efficient Text Classification with Class-based Embeddings.
Proceedings of the International Joint Conference on Neural Networks, 2019

Attention-based Adversarial Training for Seamless Nudity Censorship.
Proceedings of the International Joint Conference on Neural Networks, 2019

Language-Agnostic Visual-Semantic Embeddings.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Classification of Contractual Conflicts via Learning of Semantic Representations.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018
Order embeddings and character-level convolutions for multimodal alignment.
Pattern Recognit. Lett., 2018

Improving Action Recognition using Temporal Regions.
J. Inf. Data Manag., 2018

Adult content detection in videos with convolutional and recurrent neural networks.
Neurocomputing, 2018

Fast Self-Attentive Multimodal Retrieval.
Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision, 2018

A multi-task neural network for multilingual sentiment classification and language detection on Twitter.
Proceedings of the 33rd Annual ACM Symposium on Applied Computing, 2018

Seamless Nudity Censorship: an Image-to-Image Translation Approach based on Adversarial Training.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Evaluating the Feasibility of Deep Learning for Action Recognition in Small Datasets.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Real-Time Detection of Pedestrian Traffic Lights for Visually-Impaired People.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Hierarchical Multi-Label Classification Networks.
Proceedings of the 35th International Conference on Machine Learning, 2018

Self-Attention for Synopsis-Based Multi-Label Movie Genre Classification.
Proceedings of the Thirty-First International Florida Artificial Intelligence Research Society Conference, 2018

Bidirectional Retrieval Made Simple.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Using Scene Context to Improve Action Recognition.
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2018

Increasing Boosting Effectiveness with Estimation of Distribution Algorithms.
Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

2017
Movie genre classification: A multi-label approach based on convolutions through time.
Appl. Soft Comput., 2017

Hierarchical multi-label classification with chained neural networks.
Proceedings of the Symposium on Applied Computing, 2017

Convolutions through time for multi-label movie genre classification.
Proceedings of the Symposium on Applied Computing, 2017

A character-based convolutional neural network for language-agnostic Twitter sentiment analysis.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Deep neural networks for kitchen activity recognition.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Virtual guide dog: An application to support visually-impaired people through deep convolutional neural networks.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Leveraging deep visual features for content-based movie recommender systems.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Media Professionals' Opinions about Interactive Visualizations of Political Polarization during Brazilian Presidential Campaigns on Twitter.
Proceedings of the 50th Hawaii International Conference on System Sciences, 2017

A Deep Neural Architecture for Kitchen Activity Recognition.
Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, 2017

An Efficient Deep Neural Architecture for Multilingual Sentiment Analysis in Twitter.
Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, 2017

Estimation of distribution algorithms for decision-tree induction.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

Deep Neural Networks for Handwritten Chinese Character Recognition.
Proceedings of the 2017 Brazilian Conference on Intelligent Systems, 2017

Hybrid Activity and Plan Recognition for Video Streams.
Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Reduction strategies for hierarchical multi-label classification in protein function prediction.
BMC Bioinform., 2016

A meta-learning framework for algorithm recommendation in software fault prediction.
Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016

Medoid-based data clustering with estimation of distribution algorithms.
Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016

Movie genre classification with Convolutional Neural Networks.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Enhancing discrimination power with genetic feature construction: A grammatical evolution approach.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016

PASCAL: An EDA for parameterless shape-independent clustering.
Proceedings of the IEEE Congress on Evolutionary Computation, 2016

(Deep) Learning from Frames.
Proceedings of the 5th Brazilian Conference on Intelligent Systems, 2016

2015
Automatic Design of Decision-Tree Induction Algorithms
Springer Briefs in Computer Science, Springer, ISBN: 978-3-319-14231-9, 2015

Investigating fitness functions for a hyper-heuristic evolutionary algorithm in the context of balanced and imbalanced data classification.
Genet. Program. Evolvable Mach., 2015

Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments.
Comput. Intell. Neurosci., 2015

Evolving regression trees robust to missing data.
Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015

Evolving decision-tree induction algorithms with a multi-objective hyper-heuristic.
Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015

Hierarchical classification of Gene Ontology-based protein functions with neural networks.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Evolving balanced decision trees with a multi-population genetic algorithm.
Proceedings of the IEEE Congress on Evolutionary Computation, 2015

Clustering Molecular Dynamics Trajectories with a univariate estimation of distribution algorithm.
Proceedings of the IEEE Congress on Evolutionary Computation, 2015

A Portable OpenCL-Based Approach for SVMs in GPU.
Proceedings of the 2015 Brazilian Conference on Intelligent Systems, 2015

2014
Evolutionary Design of Decision-Tree Algorithms Tailored to Microarray Gene Expression Data Sets.
IEEE Trans. Evol. Comput., 2014

Hierarchical multi-label classification using local neural networks.
J. Comput. Syst. Sci., 2014

Evolving decision trees with beam search-based initialization and lexicographic multi-objective evaluation.
Inf. Sci., 2014

A framework for bottom-up induction of oblique decision trees.
Neurocomputing, 2014

Evolving relational hierarchical classification rules for predicting gene ontology-based protein functions.
Proceedings of the Genetic and Evolutionary Computation Conference, 2014

A grammatical evolution based hyper-heuristic for the automatic design of split criteria.
Proceedings of the Genetic and Evolutionary Computation Conference, 2014

2013
Sobre o projeto automático de algoritmos de indução de árvores de decisão.
PhD thesis, 2013

Hierarchical Bottom-Up Safe Semi-Supervised Support Vector Machines for Multi-Class Transductive Learning.
J. Inf. Data Manag., 2013

Automatic Design of Decision-Tree Algorithms with Evolutionary Algorithms.
Evol. Comput., 2013

Data stream clustering: A survey.
ACM Comput. Surv., 2013

Software effort prediction: a hyper-heuristic decision-tree based approach.
Proceedings of the 28th Annual ACM Symposium on Applied Computing, 2013

Probabilistic Clustering for Hierarchical Multi-Label Classification of Protein Functions.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

A grammatical evolution approach for software effort estimation.
Proceedings of the Genetic and Evolutionary Computation Conference, 2013

A grammatical evolution algorithm for generation of Hierarchical Multi-Label Classification rules.
Proceedings of the IEEE Congress on Evolutionary Computation, 2013

Neural Networks for Hierarchical Classification of G-Protein Coupled Receptors.
Proceedings of the Brazilian Conference on Intelligent Systems, 2013

2012
A Survey of Evolutionary Algorithms for Decision-Tree Induction.
IEEE Trans. Syst. Man Cybern. Part C, 2012

Clus-DTI: improving decision-tree classification with a clustering-based decision-tree induction algorithm.
J. Braz. Comput. Soc., 2012

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data.
BMC Bioinform., 2012

Improving the offline clustering stage of data stream algorithms in scenarios with variable number of clusters.
Proceedings of the ACM Symposium on Applied Computing, 2012

A genetic algorithm for Hierarchical Multi-Label Classification.
Proceedings of the ACM Symposium on Applied Computing, 2012

Predicting software maintenance effort through evolutionary-based decision trees.
Proceedings of the ACM Symposium on Applied Computing, 2012

A hyper-heuristic evolutionary algorithm for automatically designing decision-tree algorithms.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012

2011
Evolutionary model trees for handling continuous classes in machine learning.
Inf. Sci., 2011

Hierarchical multi-label classification for protein function prediction: A local approach based on neural networks.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

A bottom-up oblique decision tree induction algorithm.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

A clustering-based decision tree induction algorithm.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011

Towards the automatic design of decision tree induction algorithms.
Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

2010
Evolutionary model tree induction.
Proceedings of the 2010 ACM Symposium on Applied Computing (SAC), 2010

2009
Lexicographic multi-objective evolutionary induction of decision trees.
Int. J. Bio Inspired Comput., 2009

LEGAL-tree: a lexicographic multi-objective genetic algorithm for decision tree induction.
Proceedings of the 2009 ACM Symposium on Applied Computing (SAC), 2009

2008
Issues on Estimating Software Metrics in a Large Software Operation.
Proceedings of the 32nd Annual IEEE Software Engineering Workshop, 2008


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