Conferences and events
Pereira, D. C., Longo, L. C., Tosta, T. A., Martins, A. S., Silva, A. B., Rozendo, G. B., ... & do Nascimento, M. Z. (2023, June). Handcrafted features vs deep-learned features: Hermite Polynomial Classification of Liver Images. In 2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS) (pp. 495-500). IEEE. https://doi.org/10.1109/CBMS58004.2023.00268
Pereira, D. C., Longo, L. C., Tosta, T. A., Martins, A. S., Silva, A. B., Rozendo, G. B., ... & do Nascimento, M. Z. (2023, June). Handcrafted features vs deep-learned features: Hermite Polynomial Classification of Liver Images. In 2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS) (pp. 495-500). IEEE. https://doi.org/10.1109/CBMS58004.2023.00268
F. Roberto, G., C. Pereira, D., S. Martins, A., AA Tosta, T., Soares, C., Lumini, A., ... & Z. Nascimento, M. (2023, November). Detection of Covid-19 in Chest X-Ray Images Using Percolation Features and Hermite Polynomial Classification. In Iberoamerican Congress on Pattern Recognition (pp. 163-177). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-49018-7_12
Longo, L. H. D. C., Martins, A. S., Do Nascimento, M. Z., Dos Santos, L. F. S., Roberto, G. F., & Neves, L. A. (2022, June). Ensembles of fractal descriptors with multiple deep learned features for classification of histological images. In 2022 29th International Conference on Systems, Signals and Image Processing (IWSSIP) (pp. 1-4). IEEE. https://doi.org/10.1109/IWSSIP55020.2022.9854465
Dos Santos, L. F. S., Rozendo, G. B., Do Nascimento, M. Z., Tosta, T. A. A., Longo, L. H. D. C., & Neves, L. A. (2022, June). Multidimensional shannon entropy (H M) as an approach to classify H&E colorectal images. In 2022 29th International Conference on Systems, Signals and Image Processing (IWSSIP) (pp. 1-4). IEEE. https://doi.org/10.1109/IWSSIP55020.2022.9854438
Tenguam, J. J., Longo, L. H. D. C., Silva, A. B., De Faria, P. R., Do Nascimento, M. Z., & Neves, L. A. (2022, June). Classification of H&E images exploring ensemble learning with two-stage feature selection. In 2022 29th International Conference on Systems, Signals and Image Processing (IWSSIP) (pp. 1-4). IEEE. https://doi.org/10.1109/IWSSIP55020.2022.9854418
Pereira, D. C., Longo, L. C., Tosta, T. A., Martins, A. S., Silva, A. B., de Faria, P. R., Neves, L. A., Do Nascimento, M. Z. (2022, October). Classification of lymphomas images with polynomial strategy: An application with Ridge regularization. In 2022 35th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) (Vol. 1, pp. 258-263). IEEE. https://doi.org/10.1109/SIBGRAPI55357.2022.9991780
Silva, A. B., De Oliveira, C. I., Pereira, D. C., Tosta, T. A., Martins, A. S., Loyola, A. M., Cardoso, S. V., De Faria, P. R., Neves, L. A., Do Nascimento, M. Z. (2022, October). Assessment of the association of deep features with a polynomial algorithm for automated oral epithelial dysplasia grading. In 2022 35th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) (Vol. 1, pp. 264-269). IEEE. https://doi.org/10.1109/SIBGRAPI55357.2022.9991758
De Faria, T. P., Do Nascimento, M. Z., & Martins, L. G. (2021, December). Understanding the multiclass classification of lymphomas from simple descriptors. In 2021 International Conference on Computational Science and Computational Intelligence (CSCI) (pp. 1202-1208). IEEE. https://doi.org/10.1109/CSCI54926.2021.00250
Freitas, A. D., Silva, A. B., Martins, A. S., Neves, L. A., Tosta, T. A., de Faria, P. R., & do Nascimento, M. Z. (2021, November). Evaluation of normalization technique on classification with deep learning features. In Anais do XVII Workshop de Visão Computacional (pp. 107-112). SBC. https://doi.org/10.5753/wvc.2021.18898
de Faria, T. P., do Nascimento, M. Z., & Martins, L. G. (2021, November). A Method For Multiclass Lymphoma Classification Based on Morphological and Non-Morphological Descriptors. In Anais do XVII Workshop de Visão Computacional (pp. 184-189). SBC. https://doi.org/10.5753/wvc.2021.18911
dos Santos, D. F., Tosta, T. A., Silva, A. B., de Faria, P. R., Travençolo, B. A., & do Nascimento, M. Z. (2020, July). Automated nuclei segmentation on dysplastic oral tissues using cnn. In 2020 International Conference on Systems, Signals and Image Processing (IWSSIP) (pp. 45-50). IEEE. https://doi.org/10.1109/IWSSIP48289.2020.9145157
Rafael, H. D. O., Martins, A. S., Neves, L. A., & Do Nascimento, M. Z. (2020, July). Analysis of features for breast cancer recognition in different magnifications of histopathological images. In 2020 international conference on systems, signals and image processing (IWSSIP) (pp. 39-44). IEEE. https://doi.org/10.1109/IWSSIP48289.2020.9145129
dos Santos, D., Silva, A., de Faria, P., Travençolo, B., & do Nascimento, M. (2020, October). Impacts of color space transformations on dysplastic nuclei segmentation using CNN. In Anais do XVI Workshop de Visão Computacional (pp. 6-11). SBC. https://doi.org/10.5753/wvc.2020.13475
Candelero, D., Roberto, G. F., Do Nascimento, M. Z., Rozendo, G. B., & Neves, L. A. (2020, December). Selection of cnn, haralick and fractal features based on evolutionary algorithms for classification of histological images. In 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 2709-2716). IEEE. https://doi.org/10.1109/BIBM49941.2020.9313328
Silva, A. B., Dos Santos, D. F., Tosta, T. A., Martins, A. S., Neves, L. A., Travençlo, B. A., ... & do Nascimento, M. Z. (2020, December). Segmentation of Oral Epithelial Dysplasias Employing Mask R-CNN and Color Normalization. In 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 2818-2824). IEEE. https://doi.org/10.1109/BIBM49941.2020.9313101
Tenguam, J. J., Rozendo, G. B., Roberto, G. F., do Nascimento, M. Z., Martins, A. S., & Neves, L. A. (2020, December). Multidimensional and multiscale Higuchi dimension for the analysis of colorectal histological images. In 2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 2833-2839). IEEE. https://doi.org/10.1109/BIBM49941.2020.9313575
Silva, A. B., Martins, A. S., Neves, L. A., Faria, P. R., Tosta, T. A., & do Nascimento, M. Z. (2019, October). Automated nuclei segmentation in dysplastic histopathological oral tissues using deep neural networks. In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 24th Iberoamerican Congress, CIARP 2019, Havana, Cuba, October 28-31, 2019, Proceedings (pp. 365-374). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-33904-3_34
Martins, A. S., Neves, L. A., Faria, P. R., Tosta, T. A., Bruno, D. O., Longo, L. C., & do Nascimento, M. Z. (2019). Colour feature extraction and polynomial algorithm for classification of lymphoma images. In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 24th Iberoamerican Congress, CIARP 2019, Havana, Cuba, October 28-31, 2019, Proceedings 24 (pp. 262-271). Springer International Publishing. https://doi.org/10.1007/978-3-030-33904-3_24
Taino, D. F., Ribeiro, M. G., Roberto, G. F., Zafalon, G. F., do Nascimento, M. Z., Tosta, T. A., Martis, A. M., Neves, L. A. (2019). A model based on genetic algorithm for colorectal cancer diagnosis. In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 24th Iberoamerican Congress, CIARP 2019, Havana, Cuba, October 28-31, 2019, Proceedings 24 (pp. 504-513). Springer International Publishing. https://doi.org/10.1007/978-3-030-33904-3_47
Tosta, T. A., de Faria, P. R., Neves, L. A., & do Nascimento, M. Z. (2018). Fitness functions evaluation for segmentation of lymphoma histological images using genetic algorithm. In Applications of Evolutionary Computation: 21st International Conference, EvoApplications 2018, Parma, Italy, April 4-6, 2018, Proceedings 21 (pp. 47-62). Springer International Publishing. https://doi.org/10.1007/978-3-319-77538-8_4
Ribeiro, M. G., Neves, L. A., Roberto, G. F., Tosta, T. A., Martins, A. S., & Do Nascimento, M. Z. (2018, October). Analysis of the influence of color normalization in the classification of non-hodgkin lymphoma images. In 2018 31st SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) (pp. 369-376). IEEE. https://doi.org/10.1109/SIBGRAPI.2018.00054
Roberto, G. F., Do Nascimento, M. Z., Tosta, T. A. A., Neves, L. A., Ribeiro, M. G., & Martins, A. S. (2018). An investigation of jaya optimization for non-hodgkin lymphoma classification. In Workshop de Visão Computacional, Ilhéus (BA), Brazil (pp. 39-44).
Tosta, T. A., de Faria, P. R., Neves, L. A., & do Nascimento, M. Z. (2017, July). Avaliação de atributos de textura de núcleos neoplásicos para a classificação de imagens histológicas de linfoma. In Anais do XVII Workshop de Informática Médica. SBC. https://doi.org/10.5753/sbcas.2017.3728
Tosta, T. A. A., Do Nascimento, M. Z., De Faria, P. R., & Neves, L. A. (2017, June). Application of evolutionary algorithms on unsupervised segmentation of lymphoma histological images. In 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) (pp. 89-94). IEEE. https://doi.org/10.1109/CBMS.2017.69
Junior, W. L. M., do Nascimento, M. Z., & Neves, L. A. Explorando a Ripplet-II para Identificação de Lesões em Imagens Histológicas de Mama.
Neves, L. A., Pavarino, E., Cintra, A. F., Zafalon, G. F. D., Do Nascimento, M. Z., & Valêncio, C. R. (2016, December). Tetrahedral mesh segmentation based on quality criteria. In 2016 17th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT) (pp. 358-361). IEEE. https://doi.org/10.1109/PDCAT.2016.082
Neves, L. A., Pavarino, E., Souza, M. P., Valêncio, C. R., Zafalon, G. F., do Nascimento, M. Z., & Tosta, T. (2015, June). Multiscale tetrahedral meshes for fem simulations of esophageal injury. In 2015 IEEE 28th International Symposium on Computer-Based Medical Systems (pp. 103-108). IEEE. https://doi.org/10.1109/CBMS.2015.76
Tosta, T. A. A., De Abreu, A. F., Travencolo, B. A. N., do Nascimento, M. Z., & Neves, L. A. (2015, June). Unsupervised segmentation of leukocytes images using thresholding neighborhood valley-emphasis. In 2015 IEEE 28th international symposium on computer-based medical systems (pp. 93-94). IEEE. https://doi.org/10.1109/CBMS.2015.27