Conferences and events 

Santos, L. F. S. D., Neves, L. A., Martins, A. S., Roberto, G. F., Tosta, T. A. A., & Nascimento, M. Z. D. (2025). Convolutional neural networks enriched by handcrafted attributes (Enriched-CNN): an innovative approach to pattern recognition in histological images. In 27th International Conference on Enterprise Information Systems, 2025, Porto. Proceedings of the 27th International Conference on Enterprise Information Systems, 2025. p. 467-478. https://doi.org/10.5220/0013277300003929

Borgue, V. A. T., Garcia, B. L. D. O., Pelicano Junior, S. A., Roberto, G. F., Rozendo, G. B., Neves, L. A., ... & Nascimento, M. Z. D. (2025). Association of fractal geometry and data augmentation through GANs and XAI for classification of histology images. In 27th International Conference on Enterprise Information Systems, 2025, Porto. Proceedings of the 27th International Conference on Enterprise Information Systems, 2025. p. 756-762. https://doi.org/10.5220/0013280200003929

Roissmann, A. C. M., Neves, L. A., Do Nascimento, M. Z., & Tosta, T. A. (2025, June). Preprocessing techniques for public H&E histological images: a systematic review. In 2025 32nd International Conference on Systems, Signals and Image Processing (IWSSIP) (pp. 1-5). IEEE. https://doi.org/10.1109/IWSSIP66997.2025.11151972

Silva, A. B., Apumayta, J. E., Tosta, T. A., Martins, A. S., De Oliveira, D. L., Neves, L. A., ... & do Nascimento, M. Z. (2025, June). CNN ensembles for nuclei instance segmentation in OED histological images. In 2025 IEEE 38th International Symposium on Computer-Based Medical Systems (CBMS) (pp. 369-374). IEEE. https://doi.org/10.1109/CBMS65348.2025.00082

da Silva, A. F. Q., Freitas, A. D., de Faria, P. R., Neves, L. A., do Nascimento, M. Z., & Tosta, T. A. (2025, June). Color normalization by dictionary learning with nuclear segmentation evaluation in H&E histological images. In 2025 IEEE 38th International Symposium on Computer-Based Medical Systems (CBMS) (pp. 616-622). IEEE. https://doi.org/10.1109/CBMS65348.2025.00129 [source code1, source code2]

Crepaldi, G. G., de Oliveira, D. L., Tosta, T. A., Neves, L. A., Silva, A. B., Martins, A. S., & do Nascimento, M. Z. (2025, June). Nuclear segmentation in histological images using multiple attention system mixing. In 2025 IEEE 38th International Symposium on Computer-Based Medical Systems (CBMS) (pp. 154-159). IEEE. https://doi.org/10.1109/CBMS65348.2025.00041

de Oliveira, D. L., Silva, A. B., Neves, L. A., Tosta, T. A., Martins, A. S., de Faria, P. R., & do Nascimento, M. Z. (2025, June). Investigação de arquiteturas de aprendizagem profunda para segmentação de lesões em imagens histológicas. In Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS) (pp. 617-628). SBC. https://doi.org/10.5753/sbcas.2025.7688

de Oliveira, D. L., Tosta, T. A., Neves, L. A., Silva, A. B., Martins, A. S., de Faria, P. R., & do Nascimento, M. Z. (2025, September). A U-Net-Based Approach for Histological Tissue Segmentation Using RCAug Data Augmentation. In 2025 38th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) (pp. 1-6). IEEE. https://doi.org/10.1109/SIBGRAPI67909.2025.11223478 [source code, dataset]

de Albuquerque, B. C. S., Neves, L. A., do Nascimento, M. Z., & Tosta, T. A. A. (2025, September). Classification of prostate histological images using Vision Transformers: an analysis with stain normalization and ensemble learning. In Conference on Graphics, Patterns and Images (SIBGRAPI) (pp. 377-381). SBC. https://doi.org/10.5753/sibgrapi.est.2025.38333 [source code]

Roissmann, A. C. M., & Tosta, T. A. A. (2025, September). Segmentation is better when shared: a review of public H&E histological images datasets. In Conference on Graphics, Patterns and Images (SIBGRAPI) (pp. 353-359). SBC. https://doi.org/10.5753/sibgrapi.est.2025.38328

de Oliveira, D. L., de Castro, H. B., Tosta, T. A., Neves, L. A., Oliveira, P. A., de Fariall, P. R., & do Nascimento, M. Z. (2025, September). Lightweight hybrid ensemble for ameloblastoma and ameloblastic carcinoma classification. In 2025 38th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) (pp. 1-6). IEEE. https://doi.org/10.1109/SIBGRAPI67909.2025.11223358 [source code]

Carvalho, R. H., Silva, A. B., Martins, A. S., Cardoso, S. V., Freire, G. R., de Faria, P. R., ... & Do Nascimento, M. Z. (2024). Oral dysplasia classification by using fractal representation images and convolutional neural networks. Proceedings Copyright, 524, 531. https://doi.org/10.5220/0012389000003660

Lopes, T. R., Roberto, G. F., Soares, C., Tosta, T. A., Silva, A. B., Loyola, A. M., ... & Neves, L. A. (2024). Association of Grad-CAM, LIME and multidimensional fractal techniques for the classification of H&E images. Proceedings Copyright, 441, 447. https://doi.org/10.5220/0012358200003660

Fernandes, V. B., Silva, A. B., Pereira, D. C., Cardoso, S. V., de Faria, P. R., Loyola, A. M., ... & Do Nascimento, M. Z. (2024). Investigation of deep neural network compression based on Tucker decomposition for the classification of lesions in cavity oral. Proceedings Copyright, 516, 523. https://doi.org/10.5220/0012388700003660 [source code]

Miguel, P. L., Lumini, A., Medalha, G. C., Roberto, G. F., Rozendo, G. B., Cansian, A. M., ... & Neves, L. A. (2024, January). Improving explainability of the attention branch network with CAM fostering techniques in the context of histological images. In Proceedings of the 26th International Conference on Enterprise Information Systems (Vol. 1, pp. 456-464). scitepress. https://doi.org/10.5220/0012595700003690

Rozendo, G. B., Lumini, A., Roberto, G. F., Tosta, T. A. A., do Nascimento, M. Z., & Neves, L. A. (2024, January). X-GAN: Generative adversarial networks training guided with explainable artificial intelligence. In 26th International conference on enterprise information systems. https://doi.org/10.5220/0012618400003690

Soares, T. R., Silva, A. B., Loyola, A. M., Cardoso, S. V., de Faria, P. R., Neves, L. A., ... & Razente, H. (2024, June). Divergências de Bregman aplicadas na Recuperaçao por Conteudo de Imagens de Displasias Orais. In Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS) (pp. 130-141). SBC. https://doi.org/10.5753/sbcas.2024.2058

Silva, A. B., Tosta, T. A., Neves, L. A., Martins, A. S., De Faria, P. R., & Do Nascimento, M. Z. (2024, September). Ensemble of semantic segmentation models for oral epithelial dysplasia images. In 2024 37th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) (pp. 1-6). IEEE. https://doi.org/10.1109/SIBGRAPI62404.2024.10716304 [source code]

Miguel, P. L., Cansian, A. M., Rozendo, G. B., Medalha, G. C., do Nascimento, M. Z., & Neves, L. A. (2023, January). An Investigation of Deep-Learned Features for Classifying Radiographic Images of COVID-19. In 25th International Conference on Enterprise Information Systems, 2023, Prague. Proceedings of the 25th International Conference on Enterprise Information Systems, 2023. p. 675. https://doi.org/10.5220/0012038500003467

Silva, A. B., Rozendo, G. B., Tosta, T. A., Martins, A. S., Loyola, A. M., Cardoso, S. V., ... & do Nascimento, M. Z. (2023, June). CNN ensembles for nuclei segmentation on histological images of OED. In 2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS) (pp. 601-604). IEEE. https://doi.org/10.1109/CBMS58004.2023.00286

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

Neves, L. A., Martinez, J. M. C., Longo, L. H. D. C., Roberto, G. F., Tosta, T. A. A., Faria, P. R. D., ... & Rozendo, G. B. (2023). Classification of H&E images via CNN models with XAI approaches, DeepDream representations and multiple classifiers. In 25th International Conference on Enterprise Information Systems, 2023, Prague. Proceedings of the 25th International Conference on Enterprise Information Systems, 2023. p. 354. https://doi.org/10.5220/0011839400003467

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. In VIII Simpósio de Instrumentação e Imagens Médicas (SIIM) (2017), 2018, São Bernardo do Campo. Anais do VIII Simpósio de Instrumentação e Imagens Médicas (SIIM) 2017, 2017.

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