Daniel Carlos Guimarães Pedronette, Longin Jan Latecki
Journal: Information Processing & Management - Elsevier
Volume 58, Issue 2, March 2021, 102443
DOI: https://doi.org/10.1016/j.ipm.2020.102443
Related research projects:

2018/15597-6 - Application and investigation of unsupervised learning methods in retrieval and classification tasks

2017/25908-6 - Weakly supervised learning for compressed video analysis on retrieval and classification tasks for visual alert

Efficient Rank-Based Diffusion Process with Assured Convergence
Daniel Carlos Guimarães Pedronette, Lucas Pascotti Valem, Longin Jan Latecki
Journal: Journal of Imaging - MDPI
Volume 7, n. 3, March 2021, p. 49
DOI: https://doi.org/10.3390/jimaging7030049
Source code:

https://github.com/UDLF/UDLF/

https://github.com/UDLF/UDLF/blob/master/src/Methods/RDPAC.cpp
Related research projects:

2018/15597-6 - Application and investigation of unsupervised learning methods in retrieval and classification tasks

2017/25908-6 - Weakly supervised learning for compressed video analysis on retrieval and classification tasks for visual alert

2020/11366-0 - Support for computational environments and experiments execution: weakly-supervised and classification fusion methods

A rank-based framework through manifold learning for improved clustering tasks
Bionda Rozin, Vanessa Helena Pereira-Ferrero, Leonardo Tadeu Lopes, Daniel Carlos Guimarães Pedronette
Journal: Information Sciences - Elsevier
Volume 580, November 2021, Pages 202-220
DOI: https://doi.org/10.1016/j.ins.2021.08.080
Source code: https://github.com/UDLF/UDLF/
Related research projects:

2018/15597-6 - Application and investigation of unsupervised learning methods in retrieval and classification tasks

2020/02183-9 - Rank-based unsupervised learning through deep learning in diverse domains

2020/08854-2 - Investigation of graph-based contextual measures for weakly-supervised learning

2017/25908-6 - Weakly supervised learning for compressed video analysis on retrieval and classification tasks for visual alert

Unsupervised selective rank fusion for image retrieval tasks
Lucas Pascotti Valem, Daniel Carlos Guimarães Pedronette
Journal: Neurocomputing - Elsevier
Volume 377, 15 February 2020, Pages 182-199
DOI: https://doi.org/10.1016/j.neucom.2019.09.065
Source code: https://github.com/UDLF/USRF/
Related research projects:

2018/15597-6 - Application and investigation of unsupervised learning methods in retrieval and classification tasks

2017/02091-4 - Selection and combination of unsupervised learning Methods for content-based image retrieval

2017/25908-6 - Weakly supervised learning for compressed video analysis on retrieval and classification tasks for visual alert

Graph-based selective rank fusion for unsupervised image retrieval
Lucas Pascotti Valem, Daniel Carlos Guimarães Pedronette
Journal: Pattern Recognition Letters - Elsevier
Volume 135, July 2020, Pages 82-89
DOI: https://doi.org/10.1016/j.patrec.2020.03.032
Related research projects:

2018/15597-6 - Application and investigation of unsupervised learning methods in retrieval and classification tasks

2017/02091-4 - Selection and combination of unsupervised learning Methods for content-based image retrieval

2017/25908-6 - Weakly supervised learning for compressed video analysis on retrieval and classification tasks for visual alert

2013/08645-0 - Re-Ranking and rank aggregation approaches for image retrieval tasks

A framework for speaker retrieval and identification through unsupervised learning
Victor de Abreu Campos, Daniel Carlos Guimarães Pedronette
Journal: Computer Speech & Language - Elsevier
Volume 58, November 2019, Pages 153-174
DOI: https://doi.org/10.1016/j.csl.2019.04.004
Related research projects:

2018/15597-6 - Application and investigation of unsupervised learning methods in retrieval and classification tasks

2017/25908-6 - Weakly supervised learning for compressed video analysis on retrieval and classification tasks for visual alert

2015/07934-4 - Automatic speaker identification using unsupervised learning

Multimedia Retrieval Through Unsupervised Hypergraph-Based Manifold Ranking
Daniel Carlos Guimarães Pedronette, Lucas Pascotti Valem, Jurandy Almeida, Ricardo da S. Torres
Journal: IEEE Transactions on Image Processing - IEEE
Volume: 28, Issue: 12, December 2019, 5824 - 5838
DOI: http://doi.org/10.1109/TIP.2019.2920526
Source code: https://github.com/UDLF/UDLF/blob/master/src/Methods/LHRR.cpp
Related research projects:

2018/15597-6 - Application and investigation of unsupervised learning methods in retrieval and classification tasks

2017/25908-6 - Weakly supervised learning for compressed video analysis on retrieval and classification tasks for visual alert

2017/02091-4 - Selection and combination of unsupervised learning Methods for content-based image retrieval