LUCAS PASCOTTI VALEM

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Softwares

• Weakly Supervised Experiments Framework (WSEF)

  The WSEF is an open source software developed and maintained by our research team. The framework uses a rank-based model to exploit contextual information encoded in the unlabeled data in order to perform label expansion and execute a weakly supervised classification. For more information, consult the code page and our paper.
  
  

  PRESOTTO, J. G. C.; VALEM, L. P.; de SÁ, N. G.; PEDRONETTE, D. C. G.; PAPA, J. P. . Weakly Supervised Learning through Rank-based Contextual Measures. In: 2020 25th International Conference on Pattern Recognition (ICPR), 2021, pp. 5752-5759.

  Pre-Print PDF   Online Publication   Paper Presentation   Bibtex   Download Code



• Unsupervised Selective Rank Fusion (USRF)

  The USRF is an open source software developed and maintained by me under the supervision of Prof. Dr. Daniel C. G. Pedronette. A framework for ranked lists selection and fusion, completely unsupervised. For more information, consult the code page and our paper.
  
  

  VALEM, L. P. ; PEDRONETTE, D. C. G. . Unsupervised Selective Rank Fusion for Image Retrieval Tasks. In: Neurocomputing; v. 377, p. 182-199, 2019.

  Pre-Print PDF   Online Publication   Bibtex   Download Code



• Unsupervised Distance Learning Framework (UDLF)

  The UDLF is an open source software developed and maintained by me under the supervision of Prof. Dr. Daniel C. G. Pedronette. The software currently consists in the implementation of 10 different unsupervised learning methods for image retrieval. You can consult my publication and the official page for more information.
  
  VALEM, L. P. ; PEDRONETTE, D. C. G. . An Unsupervised Distance Learning Framework for Multimedia Retrieval. In: International Conference on Multimedia Retrieval (ICMR), 2017.
  Pre-Print PDF   Online Publication   Bibtex   UDLF Official Page   UDLF on Github