I am a Lectuer, part of the Data Science Research Group within Computing Science and Mathematics Division at the University of Stirling. My current research interests include machine and deep learning, pattern recognition, image processing, and remote sensing. I am currently working on different projects that combine these topics to improve understanding of a problem, helping people make informed decisions.
Conference Paper (published)
Prototypical Contrastive Network for Imbalanced Aerial Image Segmentation
Nogueira K, Maezano Faita-Pinheiro M, Ramos AP, Gonçalves WN, Marcato Junior J & Santos JAD (2023) Prototypical Contrastive Network for Imbalanced Aerial Image Segmentation. In: WACV 2024, 04.01.2024-08.01.2024. Piscataway, NJ, USA: IEEE.
Conference Paper (published)
Goncalves DN, Junior JM, Zamboni P, Pistori H, Li J, Nogueira K & Goncalves W (2023) MTLSegFormer: Multi-Task Learning With Transformers for Semantic Segmentation in Precision Agriculture. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Vancouver, BC, Canada, 18.06.2023-22.06.2023. Piscataway, NJ, USA: IEEE, pp. 6290-6298. https://doi.org/10.1109/CVPRW59228.2023.00669
Article
Johnston P, Nogueira K & Swingler K (2023) GMM-IL: Image Classification Using Incrementally Learnt, Independent Probabilistic Models for Small Sample Sizes. IEEE Access, 11, pp. 25492-25501. https://doi.org/10.1109/access.2023.3255795
Article
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, pp. 141406-141420. https://doi.org/10.1109/access.2023.3341007
Article
Souza AP, Oliveira BA, Andrade ML, Starling MCVM, Pereira AH, Maillard P, Nogueira K, dos Santos JA & Amorim CC (2023) Integrating remote sensing and machine learning to detect turbidity anomalies in hydroelectric reservoirs. Science of The Total Environment, 902, Art. No.: 165964. https://doi.org/10.1016/j.scitotenv.2023.165964
Conference Paper (published)
Paving the Way for Automatic Mapping of Rural Roads in the Amazon Rainforest
Faria LCd, Brito M, Nogueira K & dos Santos JA (2023) Paving the Way for Automatic Mapping of Rural Roads in the Amazon Rainforest. In: SIBGRAPI Conference on Graphics, Patterns and Images, 06.11.2023-09.11.2023. IEEE.
Article
Facing the Void: Overcoming Missing Data in Multi-View Imagery
Machado G, Pereira MB, Nogueira K & Dos Santos JA (2022) Facing the Void: Overcoming Missing Data in Multi-View Imagery. IEEE Access. https://doi.org/10.1109/access.2022.3231617
Article
An Introduction to Deep Morphological Networks
Nogueira K, Chanussot J, Mura MD & Dos Santos JA (2021) An Introduction to Deep Morphological Networks. IEEE Access, 9, pp. 114308-114324. https://doi.org/10.1109/access.2021.3104405
Article
AiRound and CV-BrCT: Novel Multiview Datasets for Scene Classification
Machado G, Ferreira E, Nogueira K, Oliveira H, Brito M, Gama PHT & Santos JAd (2021) AiRound and CV-BrCT: Novel Multiview Datasets for Scene Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, pp. 488-503. https://doi.org/10.1109/JSTARS.2020.3033424
Conference Paper (published)
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 IEEE International Conference on Visual Communications and Image Processing (VCIP). Visual Communications and Image Processing (VCIP 2021), Munich, 05.12.2021-08.12.2021. Piscataway, NJ, USA: IEEE. https://doi.org/10.1109/VCIP53242.2021.9675445
Article
Noninvasive Low-cost Method to Identify Armadillos' Burrows: A Machine Learning Approach
Rodrigues TF, Nogueira K & Chiarello AG (2021) Noninvasive Low-cost Method to Identify Armadillos' Burrows: A Machine Learning Approach. Wildlife Society Bulletin, 45 (3), pp. 396-401. https://doi.org/10.1002/wsb.1222
Article
Osco LP, Nogueira K, Marques Ramos AP, Faita Pinheiro MM, Furuya DEG, Gonçalves WN, de Castro Jorge LA, Marcato Junior J & dos Santos JA (2021) Semantic segmentation of citrus-orchard using deep neural networks and multispectral UAV-based imagery. Precision Agriculture, 22 (4), pp. 1171-1188. https://doi.org/10.1007/s11119-020-09777-5
Article
Semantic segmentation of tree-canopy in urban environment with pixel-wise deep learning
Martins JAC, Nogueira K, Osco LP, Gomes FDG, Furuya DEG, Gonçalves WN, Sant’ana DA, Ramos APM, Liesenberg V, dos Santos JA, de Oliveira PTS & Marcato Junior J (2021) Semantic segmentation of tree-canopy in urban environment with pixel-wise deep learning. Remote Sensing, 13 (16), Art. No.: 3054. https://doi.org/10.3390/rs13163054
Article
Zamboni P, Marcato Junior J, de Andrade Silva J, Miyoshi GT, Matsubara ET, Nogueira K & Gonçalves WN (2021) 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), Art. No.: 2482. https://doi.org/10.3390/rs13132482
Conference Paper (published)
Towards Open-Set Semantic Segmentation of Aerial Images
da Silva CCV, Nogueira K, Oliveira HN & dos Santos JA (2020) Towards Open-Set Semantic Segmentation of Aerial Images. In: 2020 IEEE Latin American GRSS and ISPRS Remote Sensing Conference, LAGIRS 2020. IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS 2020), Santiago, Chile, 21.03.2020-26.03.2020. Piscataway, NJ, USA: Institute of Electrical and Electronics Engineers Inc. pp. 16-21. https://doi.org/10.1109/LAGIRS48042.2020.9165597
Article
Facing Erosion Identification in Railway Lines Using Pixel-wise Deep-based Approaches
Nogueira K, Machado GLS, Gama PHT, Da Silva CCV, Balaniuk R & Santos JAD (2020) Facing Erosion Identification in Railway Lines Using Pixel-wise Deep-based Approaches. Remote Sensing, 12 (4), Art. No.: 739. https://doi.org/10.3390/rs12040739
Article
Dynamic Multicontext Segmentation of Remote Sensing Images Based on Convolutional Networks
Nogueira K, Dalla Mura M, Chanussot J, Schwartz WR & dos Santos JA (2019) Dynamic Multicontext Segmentation of Remote Sensing Images Based on Convolutional Networks. IEEE Transactions on Geoscience and Remote Sensing, 57 (10), pp. 7503-7520. https://doi.org/10.1109/tgrs.2019.2913861
Article
Spatio-Temporal Vegetation Pixel Classification by Using Convolutional Networks
Nogueira K, dos Santos JA, Menini N, Silva TSF, Morellato LPC & da S Torres R (2019) Spatio-Temporal Vegetation Pixel Classification by Using Convolutional Networks. IEEE Geoscience and Remote Sensing Letters, 16 (10), pp. 1665-1669. https://doi.org/10.1109/lgrs.2019.2903194
Article
Exploiting ConvNet Diversity for Flooding Identification
Nogueira K, Fadel SG, Dourado IC, Werneck RdO, Munoz JAV, Penatti OAB, Calumby RT, Li LT, dos Santos JA & Torres RdS (2018) Exploiting ConvNet Diversity for Flooding Identification. IEEE Geoscience and Remote Sensing Letters, 15 (9), pp. 1446-1450. https://doi.org/10.1109/lgrs.2018.2845549
Article
Towards better exploiting convolutional neural networks for remote sensing scene classification
Nogueira K, Penatti OAB & dos Santos JA (2017) Towards better exploiting convolutional neural networks for remote sensing scene classification. Pattern Recognition, 61, pp. 539-556. https://doi.org/10.1016/j.patcog.2016.07.001
Conference Paper (published)
Learning to semantically segment high-resolution remote sensing images
Nogueira K, Dalla Mura M, Chanussot J, Schwartz WR & dos Santos JA (2016) Learning to semantically segment high-resolution remote sensing images. In: 2016 23rd International Conference on Pattern Recognition (ICPR) Proceedings. 2016 23rd International Conference on Pattern Recognition (ICPR), Cancun, Mexico, 04.12.2016-08.12.2016. Piscataway, NJ: IEEE, pp. 3566-3571. https://doi.org/10.1109/icpr.2016.7900187
Article
Pointwise and pairwise clothing annotation: combining features from social media
Nogueira K, Veloso AA & dos Santos JA (2016) Pointwise and pairwise clothing annotation: combining features from social media. Multimedia Tools and Applications, 75 (7), pp. 4083-4113. https://doi.org/10.1007/s11042-015-3087-2
Conference Paper (published)
Do deep features generalize from everyday objects to remote sensing and aerial scenes domains?
Penatti OAB, Nogueira K & dos Santos JA (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). The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2015, Boston, MA, USA, 07.06.2015-12.06.2015. Piscataway, NJ, USA: IEEE. https://doi.org/10.1109/cvprw.2015.7301382
