L. David, H. Pedrini, and Z. Dias, “P-NOC: Adversarial CAM Generation for Weakly Supervised Semantic Segmentation,” arXiv preprint arXiv:2305.12522, 2023.
L. David et al., “Adversarial Feature Hallucination in a Supervised Contrastive Space for Few-Shot Learning of Provenance in Paintings,” in 2023 IEEE Latin American Conference on Computational Intelligence (LA-CCI), 2023, pp. 1–6.
L. David, H. Pedrini, and Z. Dias, “MinMax-CAM: Increasing Precision of Explaining Maps by Contrasting Gradient Signals and Regularizing Kernel Usage,” in International Joint Conference on Computer Vision, Imaging and Computer Graphics, 2022, pp. 222–247.
G. B. de Oliveira et al., “Bias Assessment in Medical Imaging Analysis: A Case Study on Retinal OCT Image Classification.,” in ICAART (3), 2022, pp. 574–580.
L. David, H. Pedrini, and Z. Dias, “MinMax-CAM: Improving Focus of CAM-based Visualization Techniques in Multi-label Problems,” in 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2022, vol. 4, pp. 106–117.
L. O. David, H. Pedrini, Z. Dias, and A. Rocha, “Authentication of Vincent van Gogh’s work,” in International Conference on Computer Analysis of Images and Patterns, 2021, pp. 371–380.
L. David, H. Pedrini, Z. Dias, and A. Rocha, “Connoisseur: provenance analysis in paintings,” in 2021 IEEE Symposium Series on Computational Intelligence (SSCI), 2021, pp. 1–8.
L. O. David, “A Study of the ISOMAP Algorithm and Its Applications in Machine Learning,” 2015.
