Publications
2024
Automatic mapping of high-risk urban areas for Aedes aegypti infestation based on building facade image analysis.
Laranjeira, C., Pereira, M., Oliveira, R., Barbosa, G., Fernandes, C., Bermudi, P., . . . Chiaravalloti-Neto, F. (2024). Automatic mapping of high-risk urban areas for Aedes aegypti infestation based on building facade image analysis.. PLoS neglected tropical diseases, 18(6), e0011811. doi:10.1371/journal.pntd.0011811
Prototypical Contrastive Network for Imbalanced Aerial Image Segmentation
Nogueira, K., Faita-Pinheiro, M. M., Marques Ramos, A. P., Gonçalves, W. N., Junior, J. M., & Dos Santos, J. A. (2024). Prototypical Contrastive Network for Imbalanced Aerial Image Segmentation. In 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (pp. 8351-8361). IEEE. doi:10.1109/wacv57701.2024.00818
Better, Not Just More: Data-centric machine learning for Earth observation
Roscher, R., Russwurm, M., Gevaert, C., Kampffmeyer, M., Dos Santos, J. A., Vakalopoulou, M., . . . Tuia, D. (2024). Better, Not Just More: Data-centric machine learning for Earth observation. IEEE Geoscience and Remote Sensing Magazine, 12(4), 335-355. doi:10.1109/mgrs.2024.3470986
2023
Integrating remote sensing and machine learning to detect turbidity anomalies in hydroelectric reservoirs.
Souza, A. P., Oliveira, B. A., Andrade, M. L., Starling, M. C. V. M., Pereira, A. H., Maillard, P., . . . Amorim, C. C. (2023). Integrating remote sensing and machine learning to detect turbidity anomalies in hydroelectric reservoirs.. The Science of the total environment, 902, 165964. doi:10.1016/j.scitotenv.2023.165964
Paving the Way for Automatic Mapping of Rural Roads in the Amazon Rainforest
de Faria, L. C., Brito, M., Nogueira, K., & dos Santos, J. A. (2023). Paving the Way for Automatic Mapping of Rural Roads in the Amazon Rainforest. In 2023 36th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) (pp. 1-6). IEEE. doi:10.1109/sibgrapi59091.2023.10347153
Fully convolutional open set segmentation
Oliveira, H., Silva, C., Machado, G. L. S., Nogueira, K., & dos Santos, J. A. (2023). Fully convolutional open set segmentation. Machine Learning, 112(5), 1733-1784. doi:10.1007/s10994-021-06027-1
Facing the Void: Overcoming Missing Data in Multi-View Imagery
Machado, G., Pereira, M. B., Nogueira, K., & Santos, J. A. D. (2023). Facing the Void: Overcoming Missing Data in Multi-View Imagery. IEEE Access, 11, 12547-12554. doi:10.1109/access.2022.3231617
GMM-IL: Image Classification Using Incrementally Learnt, Independent Probabilistic Models for Small Sample Sizes
Johnston, P., Nogueira, K., & Swingler, K. (2023). GMM-IL: Image Classification Using Incrementally Learnt, Independent Probabilistic Models for Small Sample Sizes. IEEE Access, 11, 25492-25501. doi:10.1109/access.2023.3255795
MTLSegFormer: Multi-task Learning with Transformers for Semantic Segmentation in Precision Agriculture
Goncalves, D. N., Marcato, J., Zamboni, P., Pistori, H., Li, J., Nogueira, K., & Goncalves, W. N. (2023). MTLSegFormer: Multi-task Learning with Transformers for Semantic Segmentation in Precision Agriculture. In 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (pp. 6290-6298). IEEE. doi:10.1109/cvprw59228.2023.00669
NS-IL: Neuro-Symbolic Visual Question Answering Using Incrementally Learnt, Independent Probabilistic Models for Small Sample Sizes
Johnston, P., Nogueira, K., & Swingler, K. (2023). NS-IL: Neuro-Symbolic Visual Question Answering Using Incrementally Learnt, Independent Probabilistic Models for Small Sample Sizes. IEEE Access, 11, 141406-141420. doi:10.1109/access.2023.3341007
2021
Security and Forensics Exploration of Learning-based Image Coding
Bhowmik, D., Elawady, M., & Nogueira, K. (2021). Security and Forensics Exploration of Learning-based Image Coding. In 2021 International Conference on Visual Communications and Image Processing (VCIP) (pp. 1-5). IEEE. doi:10.1109/vcip53242.2021.9675445
Noninvasive Low‐cost Method to Identify Armadillos' Burrows: A Machine Learning Approach
Rodrigues, T. F., Nogueira, K., & Chiarello, A. G. (2021). Noninvasive Low‐cost Method to Identify Armadillos' Burrows: A Machine Learning Approach. Wildlife Society Bulletin, 45(3), 396-401. doi:10.1002/wsb.1222
Semantic Segmentation of Tree-Canopy in Urban Environment with Pixel-Wise Deep Learning
Martins, J. A. C., Nogueira, K., Osco, L. P., Gomes, F. D. G., Furuya, D. E. G., Gonçalves, W. N., . . . Junior, J. M. (n.d.). Semantic Segmentation of Tree-Canopy in Urban Environment with Pixel-Wise Deep Learning. Remote Sensing, 13(16), 3054. doi:10.3390/rs13163054
Semantic segmentation of citrus-orchard using deep neural networks and multispectral UAV-based imagery
Osco, L. P., Nogueira, K., Marques Ramos, A. P., Faita Pinheiro, M. M., Furuya, D. E. G., Gonçalves, W. N., . . . dos Santos, J. A. (2021). Semantic segmentation of citrus-orchard using deep neural networks and multispectral UAV-based imagery. Precision Agriculture, 22(4), 1171-1188. doi:10.1007/s11119-020-09777-5
Segmentation of Tree Canopies in Urban Environments Using Dilated Convolutional Neural Network
Martins, J., Nogueira, K., Zamboni, P., de Oliveira, P. T. S., Goncalves, W. N., dos Santos, J. A., & Marcato, J. (2021). Segmentation of Tree Canopies in Urban Environments Using Dilated Convolutional Neural Network. In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS (pp. 6932-6935). IEEE. doi:10.1109/igarss47720.2021.9553218
Benchmarking Anchor-Based and Anchor-Free State-of-the-Art Deep Learning Methods for Individual Tree Detection in RGB High-Resolution Images
Zamboni, P., Junior, J. M., Silva, J. D. A., Miyoshi, G. T., Matsubara, E. T., Nogueira, K., & Gonçalves, W. N. (n.d.). Benchmarking Anchor-Based and Anchor-Free State-of-the-Art Deep Learning Methods for Individual Tree Detection in RGB High-Resolution Images. Remote Sensing, 13(13), 2482. doi:10.3390/rs13132482
AiRound and CV-BrCT: Novel Multiview Datasets for Scene Classification
Machado, G., Ferreira, E., Nogueira, K., Oliveira, H., Brito, M., Gama, P. H. T., & Santos, J. A. D. (2021). AiRound and CV-BrCT: Novel Multiview Datasets for Scene Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 488-503. doi:10.1109/jstars.2020.3033424
An Introduction to Deep Morphological Networks
Nogueira, K., Chanussot, J., Mura, M. D., & Santos, J. A. D. (2021). An Introduction to Deep Morphological Networks. IEEE Access, 9, 114308-114324. doi:10.1109/access.2021.3104405
2020
Towards Open-Set Semantic Segmentation Of Aerial Images
da Silva, C. C. V., Nogueira, K., Oliveira, H. N., & Santos, J. A. D. (2020). Towards Open-Set Semantic Segmentation Of Aerial Images. In 2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS). IEEE. doi:10.1109/lagirs48042.2020.9165597
Facing Erosion Identification in Railway Lines Using Pixel-Wise Deep-Based Approaches
Nogueira, K., L. S. Machado, G., H. T. Gama, P., C. V. da Silva, C., Balaniuk, R., & A. dos Santos, J. (n.d.). Facing Erosion Identification in Railway Lines Using Pixel-Wise Deep-Based Approaches. Remote Sensing, 12(4), 739. doi:10.3390/rs12040739
2019
Dynamic Multicontext Segmentation of Remote Sensing Images Based on Convolutional Networks
Nogueira, K., Dalla Mura, M., Chanussot, J., Schwartz, W. R., & dos Santos, J. A. (2019). Dynamic Multicontext Segmentation of Remote Sensing Images Based on Convolutional Networks. IEEE Transactions on Geoscience and Remote Sensing, 57(10), 7503-7520. doi:10.1109/tgrs.2019.2913861
Spatio-Temporal Vegetation Pixel Classification by Using Convolutional Networks
Nogueira, K., dos Santos, J. A., Menini, N., Silva, T. S. F., Morellato, L. P. C., & Torres, R. D. S. (2019). Spatio-Temporal Vegetation Pixel Classification by Using Convolutional Networks. IEEE Geoscience and Remote Sensing Letters, 16(10), 1665-1669. doi:10.1109/lgrs.2019.2903194
A Tool for Bridge Detection in Major Infrastructure Works Using Satellite Images
Nogueira, K., Cesar, C., Gama, P. H. T., Machado, G. L. S., & dos Santos, J. A. (2019). A Tool for Bridge Detection in Major Infrastructure Works Using Satellite Images. In 2019 XV Workshop de Visão Computacional (WVC) (pp. 72-77). IEEE. doi:10.1109/wvc.2019.8876942
2018
Exploiting ConvNet Diversity for Flooding Identification
Nogueira, K., Fadel, S. G., Dourado, I. C., de O. Werneck, R., Munoz, J. A. V., Penatti, O. A. B., . . . Torres, R. D. S. (2018). Exploiting ConvNet Diversity for Flooding Identification. IEEE Geoscience and Remote Sensing Letters, 15(9), 1446-1450. doi:10.1109/lgrs.2018.2845549
2017
Deep contextual description of superpixels for aerial urban scenes classification
Santana, T. M. H. C., Nogueira, K., Machado, A. M. C., & dos Santos, J. A. (2017). Deep contextual description of superpixels for aerial urban scenes classification. In 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 3027-3031). IEEE. doi:10.1109/igarss.2017.8127636
Semantic segmentation of vegetation images acquired by unmanned aerial vehicles using an ensemble of ConvNets
Nogueira, K., dos Santos, J. A., Cancian, L., Borges, B. D., Silva, T. S. F., Morellato, L. P., & Torres, R. D. S. (2017). Semantic segmentation of vegetation images acquired by unmanned aerial vehicles using an ensemble of ConvNets. In 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 3787-3790). IEEE. doi:10.1109/igarss.2017.8127824
Learning Deep Features on Multiple Scales for Coffee Crop Recognition
Baeta, R., Nogueira, K., Menotti, D., & dos Santos, J. A. (2017). Learning Deep Features on Multiple Scales for Coffee Crop Recognition. In 2017 30th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI) (pp. 262-268). IEEE. doi:10.1109/sibgrapi.2017.41
Data-Driven flood detection using neural networks
Nogueira, K., Fadel, S. G., Dourado, I. C., De Werneck, R. O., Munoz, J. A., Penatti, O. A. B., . . . Torres, R. D. S. (2017). Data-Driven flood detection using neural networks. In CEUR Workshop Proceedings Vol. 1984.
Towards better exploiting convolutional neural networks for remote sensing scene classification
Nogueira, K., Penatti, O. A. B., & dos Santos, J. A. (2017). Towards better exploiting convolutional neural networks for remote sensing scene classification. Pattern Recognition, 61, 539-556. doi:10.1016/j.patcog.2016.07.001
2016
Towards vegetation species discrimination by using data-driven descriptors
Nogueira, K., Dos Santos, J. A., Fornazari, T., Freire Silva, T. S., Morellato, L. P., & S. Torres, R. D. (2016). Towards vegetation species discrimination by using data-driven descriptors. In 2016 9th IAPR Workshop on Pattern Recogniton in Remote Sensing (PRRS) (pp. 1-6). IEEE. doi:10.1109/prrs.2016.7867024
Pointwise and pairwise clothing annotation: combining features from social media
Nogueira, K., Veloso, A. A., & dos Santos, J. A. (2016). Pointwise and pairwise clothing annotation: combining features from social media. Multimedia Tools and Applications, 75(7), 4083-4113. doi:10.1007/s11042-015-3087-2
Learning to semantically segment high-resolution remote sensing images
Nogueira, K., Dalla Mura, M., Chanussot, J., Schwartz, W. R., & dos Santos, J. A. (2016). Learning to semantically segment high-resolution remote sensing images. In 2016 23rd International Conference on Pattern Recognition (ICPR) (pp. 3566-3571). IEEE. doi:10.1109/icpr.2016.7900187
RECOD @ Placing task of MediaEval 2016: A ranking fusion approach for geographic-location prediction of multimedia objects
Muñoz, J. A. V., Li, L. T., Dourado, Í. C., Nogueira, K., Fadel, S. G., Penatti, O. A. B., . . . Da Torres, R. S. (2016). RECOD @ Placing task of MediaEval 2016: A ranking fusion approach for geographic-location prediction of multimedia objects. In CEUR Workshop Proceedings Vol. 1739.
2015
Improving Spatial Feature Representation from Aerial Scenes by Using Convolutional Networks
Nogueira, K., Miranda, W. O., & Dos Santos, J. A. (2015). Improving Spatial Feature Representation from Aerial Scenes by Using Convolutional Networks. In 2015 28th SIBGRAPI Conference on Graphics, Patterns and Images (pp. 289-296). IEEE. doi:10.1109/sibgrapi.2015.39
Do deep features generalize from everyday objects to remote sensing and aerial scenes domains?
Penatti, O. A. B., Nogueira, K., & dos Santos, J. A. (2015). Do deep features generalize from everyday objects to remote sensing and aerial scenes domains?. In 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (pp. 44-51). IEEE. doi:10.1109/cvprw.2015.7301382
Coffee Crop Recognition Using Multi-scale Convolutional Neural Networks
Nogueira, K., Schwartz, W. R., & dos Santos, J. A. (2015). Coffee Crop Recognition Using Multi-scale Convolutional Neural Networks. In Unknown Conference (pp. 67-74). Springer International Publishing. doi:10.1007/978-3-319-25751-8_9
RECOD @ placing task of MediaEval 2015
Li, L. T., Muñoz, J. A. V., Almeida, J., Calumby, R. T., Penatti, O. A. B., Dourado, Í. C., . . . Da Torres, R. (2015). RECOD @ placing task of MediaEval 2015. In CEUR Workshop Proceedings Vol. 1436.
2014
Learning to Annotate Clothes in Everyday Photos: Multi-modal, Multi-label, Multi-instance Approach
Veloso, A. A., Dos Santos, J. A., & Nogueira, K. (2014). Learning to Annotate Clothes in Everyday Photos: Multi-modal, Multi-label, Multi-instance Approach. In 2014 27th SIBGRAPI Conference on Graphics, Patterns and Images (pp. 327-334). IEEE. doi:10.1109/sibgrapi.2014.37