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 | Full Professor Computer Science Department of Statistics, Applied Mathematics and Computing (DEMAC) São Paulo State University (UNESP) Education 2009-2012: PhD in Computer Science, Institute of Computing, UNICAMP 2006-2008: MsC in Computer Science, Institute of Computing, UNICAMP 2001-2005: BSc in Computer Science, DEMAC, UNESP Research Information Retrieval; Content-Based Image Retrieval; Re-Ranking; Rank Aggregation; Unsupervised Learning; Semi-Supervised Learning; Parallel Computing |
I received my B.Sc. in Computer Science from São Paulo State University (UNESP), Brazil, in 2005, and my M.Sc. and Ph.D. in Computer Science from the University of Campinas (UNICAMP), Brazil, in 2008 and 2012, respectively. I am currently a Full Professor in the Department of Statistics, Applied Mathematics and Computing at São Paulo State University (UNESP) and a former Collaborating Researcher at the Institute of Computing - UNICAMP. I also serve as an Associate Editor of Pattern Recognition published by Elsevier.
Context-Aware Interpretable Representations for Retrieval and Graph Convolutional Network Classification
ALMEIDA, T. C. C. ; LETICIO, GUSTAVO ROSSETO ; KAWAI, V. A. S. ; PEDRONETTE, D.C.G Context-Aware Interpretable Representations for Retrieval and Graph Convolutional Network Classification., In: ACM International Conference on Multimedia Retrieval (ICMR) - 2026. [Code]
Self-Supervised Clustering based on Manifold Learning and Graph Convolutional Networks
LOPES, L. T. ; PEDRONETTE, DANIEL C. G. Self-Supervised Clustering based on Manifold Learning and Graph Convolutional Networks., In: IEEE Winter Conference on Applications of Computer Vision (WACV) - 2023. [Code] [Supplementary Material]
Rank Flow Embedding for Unsupervised and Semi-Supervised Manifold Learning
VALEM, L. P. ; PEDRONETTE, DANIEL C. G. ; LATECKI, L. J. . Rank Flow Embedding for Unsupervised and Semi-Supervised Manifold Learning., IEEE Transactions on Image Processing, 2023.
[Code UDLF - C++] [Code Python - pyUDLF] [Arxiv pdf]pyUDLF: A Python Framework for Unsupervised Distance Learning Tasks
LETICIO, G. R.; VALEM, L. P.; LOPES, L. T.; PEDRONETTE, DANIEL C. G. . pyUDLF: A Python Framework for Unsupervised Distance Learning Tasks., ACM Multimedia, 2023.
[Code] [Presentation]A BFS-Tree of Ranking References for Unsupervised Manifold Learning
PEDRONETTE, D. C. G.; VALEM, L. P.; TORRES, R. S. . A BFS-Tree of Ranking References for Unsupervised Manifold Learning., Pattern Recognition, 2021.
Rank-based self-training for graph convolutional networks
PEDRONETTE, D. C. G.; LATECKI, L. J. . Rank-based self-training for graph convolutional networks., Information Processing and Management, 2021.
Multimedia Retrieval Through Unsupervised Hypergraph-Based Manifold Ranking.
PEDRONETTE, D. C. G.; VALEM, L. P.; ALMEIDA, J., TORRES, R. S. . Multimedia Retrieval Through Unsupervised Hypergraph-Based Manifold Ranking., IEEE Transactions on Image Processing, 2019.
Unsupervised Manifold Learning through Reciprocal kNN Graph and Connected Components for Image Retrieval Tasks
PEDRONETTE, D. C. G.; GONÇALVES, F. M. F.; GUILHERME, I. R. . Unsupervised Manifold Learning through Reciprocal kNN Graph and Connected Components for Image Retrieval Tasks, Pattern Recognition, 2018.
* Rank-based Unsupervised Learning
for Image Retrieval
Seminar at Polytechnique Montréal, 2022
* Lecture: Unsupervised Distance Learning for Image Retrieval
Presented at following universities:Institute of Science and Technology (ICT), Federal University of São Paulo (UNIFESP), 2020.
Instituto de Ciências Matemáticas e de Computação (ICMC), University of São Paulo (USP), 2019.
Department of Computer Science (DCC), Federal University of Minas Gerais (UFMG), 2015.
Institute of Computing (IC), University of Campinas (UNICAMP), 2015.
