Research groups
I have worked in three main research groups:
-
2016-2020: Bio-Inspired Computer Laboratory (LABCIN)
-
2019-2020: Hierarchical Anticipatory Learning Laboratory (HALLab), Dalhousie University
-
2013-2016: Optimization Laboratory (LabOtim), Federal University of Espírito Santo
Currently, I work with the Samsung R&D group in Brazil, with focus in AI applied to healthcare.
List of publications
This is my list of publications. It’s organized in chronological time. You can also check my Google Scholar.
Learning multiplane images from single views with self-supervision
- Authors: Gustavo S. P. Carvalho, Diogo C. Luvizon, Antonio Joia, Andre G. C. Pacheco, Otavio A. B. Penatti
- In: British Machine Vision Conference (BMVC) 2021
- Download: paper – page – presentation
Improving Deep Learning Sound Events Classifiers Using Gram Matrix Feature-Wise Correlations
- Authors: Antonio Joia, Andre Pacheco, and Diogo Luvizon
- In: IEEE International Conference on Acoustics, Speech and Signal Processing
- Download: paper – code
An attention-based mechanism to combine images and metadata in deep learning models applied to skin cancer classification
- Authors: Andre Pacheco and Renato Krohling
- In: IEEE Journal of Biomedical and Health Informatics
- Download: paper – code
Improving Deep Learning Sound Events Classifiers using Gram Matrix Feature-wise Correlations
- Authors: Antonio Joia Neto, Andre G. C. Pacheco, Diogo Carbonera Luvizon
- In: IEEE International Conference on Acoustics, Speech and Signal Processing
- Download: paper – code – presentation
On Out-of-Distribution Detection Algorithms With Deep Neural Skin Cancer Classifiers
- Best paper award 🥇
- Authors: Andre Pacheco, Chandramouli Sastry, Thomas Trappenberg, Sageev Oore, and Renato Krohling
- In: IEEE computer society conference on Computer Vision and Pattern Recognition 2020 @ ISIC 2020 workshop
- Download: paper – code – presentation
Learning dynamic weights for an ensemble of deep models applied to medical imaging classification
- Authors: Andre Pacheco, Thomas Trappenberg, and Renato Krohling
- In: IEEE International Joint Conference in Neural Networks, 2020
- Download: paper
An App to Detect Melanoma Using Deep Learning: An Approach to Handle Imbalanced Data Based on Evolutionary Algorithms.
- Authors: Pedro Castro, Breno Krohling, Andre Pacheco, and Renato Krohling
- In: IEEE International Joint Conference in Neural Networks, 2020
- Download: paper
Skin lesion segmentation using deep learning for images acquired from smartphones
- Authors: Gabriel de Angelo, Andre Pacheco, and Renato Krohling
- In: IEEE International Joint Conference in Neural Networks 2019.
- Download: paper
Skin cancer detection based on deep learning and entropy to detect outlier samples
- Authors: Andre Pacheco, Alib Abder, and Thomas Trappenberg
- In: MICCAI 2019 @ ISIC Challenge, 2019
- Download: paper – code
Recent advances in deep learning applied to skin cancer detection
- Authors: Andre Pacheco and Renato Krohling
- In: NeurIPS 2019 @ Retrospectives workshop
- Download: paper – presentation
Aggregation of neural classifiers using Choquet integral with respect to a fuzzy measure
- Authors: Andre Pacheco and Renato Krohling
- In: Neurocomputing, 2020
- Download: paper
Ranking of Classification Algorithms in Terms of Mean–Standard Deviation Using A-TOPSIS
- Authors: Andre Pacheco and Renato Krohling
- In: Annals of Data Science, 2016
- Download: paper
An approach to improve online sequential extreme learning machines using a restricted Boltzmann machine
- Authors: Andre Pacheco and Renato Krohling
- In: IEEE International Joint Conference in Neural Networks, 2018
- Download: paper – code
Restricted Boltzmann machine to determine the input weights for extreme learning machines
- Authors: Andre Pacheco, Carlos Silva, and Renato Krohling
- In: Expert Systems with Applications, 2018
- Download: paper – code
Ranking of classification algorithms in terms of mean-standard deviation using A-TOPSIS
- Authors: Andre Pacheco and Renato Krohling
- In: Annals of data Science, 2018
- Download: paper
TODIM and TOPSIS with Z-numbers
- Authors: Renato Krohling, Andre Pacheco, and Guilherme Artém
- In: Frontiers of Information Technology & Electronic Engineering, 2017
- Download: paper
Agregação de elenco de classificadores utilizando integral de Choquet com respeito a medida λ-fuzzy
- Authors: Renato Krohling, Andre Pacheco, and Guilherme Artém
- In: Simpósio Brasileiro de Pesquisa Operacional, 2016
- Download: paper
Classificação de grandes bases de dados utilizando máquina de Boltzmann restrita discriminativa,
- Authors: Renato Krohling, Andre Pacheco, and Guilherme Artém
- In: Simpósio Brasileiro de Pesquisa Operacional, 2016
- Download: paper
A-TOPSIS – An approach Based on TOPSIS for Ranking Evolutionary Algorithms
- Authors: Renato Krohling and Andre Pacheco
- In: Procedia Computer Science, 2015
- Download: paper – code
Time Series Prediction using Restricted Boltzmann Machines and backpropagation
- Authors: Rafael Hrasko, Andre Pacheco, and Renato Krohling
- In: Procedia Computer Science, 2015
- Download: paper
Interval-valued Intuitionistic Fuzzy TODIM
- Authors: Renato Krohling and Andre Pacheco
- In: Procedia Computer Science, 2014
- Download: paper
IF-TODIM: An intuitionistic fuzzy TODIM to multi-criteria decision making
- Authors: Renato Krohling, Andre Pacheco, and Andre Siviero
- In: Knowledge-Based Systems, 2013
- Download: paper
IFG-TODIM: An intuitionstic fuzzy TODIM for group decision making
- Authors: Renato Krohling and Andre Pacheco
- In: Simpósio Brasileiro de Pesquisa Operacional, 2013
- Download: paper
Talks and presentations
- Jul 2020: On Out-of-Distribution Detection Algorithms With Deep Neural Skin Cancer Classifiers. CVPR 2020 @ ISIC 2020. Download
- Dec 2019: Recent advances in deep learning applied to skin cancer detection. NeurIPS 2019 @ Retrospectives workshop. Download
- Mar 2019: Introduction to machine learning. Faculdade Multivix, Vitória, Brazil. Portuguese only. Download
- Nov 2018: Introduction to Capsule Networks. Computer Science, UFES, Vitória, Brazil. Download
- Nov 2018: Introduction to Helmholtz machine. Computer Science, UFES, Vitória, Brazil. Download
- Jun 2018: An approach to improve online sequential extreme learning machines using restricted Boltzmann machines. IJCNN 2018, Rio de Janeiro, Brazil. Download
- Apr 2018: Restricted Boltzmann Machine for clustering data. Computer Science, UFES, Vitória, Brazil. Download
- Mar 2018: Introduction to Python for scientific computer. Production Engineer, UFES, Vitória, Brazil. Portuguese only. Download
- Sep 2017: Overview of singular value decomposition. Computer Science, UFES. Vitória, UFES. Portuguese only. Download
- Apr 2017: Classification fusion. Computer Science, UFES, Vitória, Brazil. Portuguese only. Download
- Jul 2016: Restricted Boltzmann Machine for classification. SBPO 2016. Vitória, Brazil. Portuguese only. Download
- Jul 2016: Introduction to data classification. Jornada de Atualização em Computação, Elétrica e Eletrônica - JAACE, UFES, Vitória, Brazil. Portuguese only. Download
- Aug 2014: Raking algorithms with A-TOPSIS. ITQM 2014, Rio de Janeiro, Brazil. Download