Articles

Journals

  1. M. P. Nascimento, M. P. Véstias and G. Martín, “Hyperspectral Compressive Sensing With a System-On-Chip FPGA,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 3701-3710, 2020, https://doi.org/10.1109/JSTARS.2020.2996679
  2. Pereira J, Mendes J, Júnior JSS, Viegas C, Paulo JR. A Review of Genetic Algorithm Approaches for Wildfire Spread Prediction Calibration. Mathematics. 2022; 10(3):300. https://doi.org/10.3390/math10030300
  3. Júnior, J. S., Paulo, J. R., Mendes, J., Alves, D., Ribeiro, L. M., & Viegas, C. (2022). Automatic forest fire danger rating calibration: Exploring clustering techniques for regionally customizable fire danger classification. Expert Systems with Applications, 116380. https://doi.org/10.1016/j.eswa.2021.116380
  4. Viegas, D. X. F. C., Raposo, J. R. N., Ribeiro, C. F. M., Reis, L. C. D., Abouali, A., & Viegas, C. X. P. (2021). On the non-monotonic behaviour of fire spread. International journal of wildland fire, 30(9), 702-719. https://doi.org/10.1071/WF21016
  5. G. Perrolas, M. Niknejad, R. Ribeiro, and A. Bernardino. “Scalable Fire and Smoke Segmentation from Aerial Images Using Convolutional Neural Networks and Quad-Tree Search”. Sensors 22(5), 1701, 2022. https://doi.org/10.3390/s22051701
  6. B. Santana, EK Cherif, A. Bernardino, Ricardo Ribeiro, “Real Time Georeferencing of Fire Front Aerial Images using Iterative Ray-Tracing and the Bearings-Range Extended Kalman Filter”, Sensors 22(3), 1150, 2022. https://doi.org/10.3390/s22031150
  7. B. Trenčanová, V. Proença, A. Bernardino. Development of Semantic Maps of Vegetation Cover from UAV Images to Support Planning and Management in Fine-Grained Fire-Prone Landscapes. Remote Sensing. 2022; 14(5):1262. https://doi.org/10.3390/rs14051262
  8. Fire images classification based on a handcraft approach, H. Harkat, J. M. P. Nascimento, A. Bernardino, H. F. T. Ahmed, Expert Systems with Applications, February 2023, https://doi.org/10.1016/j.eswa.2022.118594
  9. Assessing the Impact of the Loss Function and Encoder Architecture for Fire Aerial Images Segmentation Using Deeplabv3+. H. Harkat, J. M. P. Nascimento, A. Bernardino, H. F. T. Ahmed, Remote Sens. 2022, 14, 2023. https://doi.org/10.3390/rs14092023
  10. Mohammadpour, P.; Viegas, D.X.; Viegas, C. Vegetation Mapping with Random Forest Using Sentinel 2 and GLCM Texture Feature—A Case Study for Lousã Region, Portugal. Remote Sens. 2022, 14, 4585. https://doi.org/10.3390/rs14184585

International Conferences

  1. H. Harkat, J. Nascimento, A. Bernardino, “Fire segmentation using a DeepLabv3+ architecture,” Proc. SPIE 11533, Image and Signal Processing for Remote Sensing XXVI, 115330M (20 September 2020); https://doi.org/10.1117/12.2573902
  2. Verlekar T.T., Bernardino A.  “Video Based Fire Detection Using Xception and Conv-LSTM”. In: Bebis G. et al. (eds) Advances in Visual Computing. ISVC 2020. Lecture Notes in Computer Science, vol 12510. Springer, Cham. https://doi.org/10.1007/978-3-030-64559-5_21
  3. H. Harkat, J.M.P. Nascimento, and A. Bernardino. “Fire Detection using Residual Deeplabv3+ Model”. ConfTele 2021. https://doi.org/10.1109/ConfTELE50222.2021.9435459
  4. H. Harkat, J.M.P. Nascimento, and A. Bernardino, “Fire Segmentation Using a SqueezeSegv2”. Image and Signal Processing for Remote Sensing XXVII, SPIE Remote Sensing, 2021. https://doi.org/10.1117/12.2598566
  5. H. Harkat, J.M.P. Nascimento, and A. Bernardino. “Fire Detection using Deeplabv3+ with Mobilenetv2”, International Geoscience and Remote Sensing Symposium, 2021. https://doi.org/10.1109/IGARSS47720.2021.9553141
  6. M. Niknejad and A. Bernardino. “Attention on Classification for Fire Segmentation”. ICMLA 2021. https://arxiv.org/abs/2111.03129
  7. Fire image detection based on clustering data mining techniques. H. Harkat, J. Nascimento, A. Bernardino, and H. Farhana Thariq Ahmed. Proc. SPIE 12267, Image and Signal Processing for Remote Sensing XXVIII, 122670D (26 October 2022); https://doi.org/10.1117/12.2636268
  8. Weakly Supervised Fire and Smoke Segmentation with CAM and CRF, B. Amaral, M. Niknejad, C. Barata, A. Bernardino. ICPR 2022. https://doi.org/10.1109/ICPR56361.2022.9956288
  9. Real-time Georeferencing of Fire Front Aerial Images using Structure from motion and Iterative Closest Point. F. Sargento, R. Ribeiro, E. K. Cherif and A. Bernardino. Workshop on Image Analysis for Forest Environmental Monitoring, ICPR 2022. https://drive.google.com/file/d/1kChBmI8H3BNxaholxNfvD24CEkbtzau3/view?usp=share_link
  10. Forest Fires Identification Using Self-Supervised Learning. S. Fernandes, M. Niknejad, C. Barata and A. Bernardino. Workshop on Image Analysis for Forest Environmental Monitoring, ICPR 2022. https://drive.google.com/file/d/1DDj6-pXnyKRxWLroKugHX_8FG6qZlbNv/view?usp=share_link
  11. An Adversarial method for Semi-supervised Segmentation of Smoke and Fire in Images. L. Kuhlmann, M. Niknejad, C. Barata, A. Bernardino and G. Zhang. Workshop on Image Analysis for Forest Environmental Monitoring, ICPR 2022. https://drive.google.com/file/d/11Vu4mJWE32s9l72dUDl_7lhOozzl10r5/view?usp=share_link
  12. Towards the Automation of Wildfire Monitoring with Aerial Vehicles: The FIREFRONT Project. R. Ribeiro, A. Bernardino, G. Cruz, D. Silva, L. Felix, J. Caetano, D. Folgado, J. Francisco, N. Simões, C. Viegas, D. Viegas, H. Harkat and J. Nascimento. Workshop on Image Analysis for Forest Environmental Monitoring, ICPR 2022. https://drive.google.com/file/d/1qyCS-BVtWsAYPIJRX-vdUbFhJvTyXVmd/view?usp=share_link
  13. A Multilayer Approach to Wildfire Aerial Thermal Image Segmentation Using Unsupervised Methods, T. Garcia, A. Bernardino, R. Ribeiro, Proc. of the 9th International Conference on Forest Fire Research, 2022. https://doi.org/10.14195/978-989-26-2298-9_4 
  14. H. Harkat, J. Nascimento, A. Bernardino Bernardino, H. Ahmed, Fire images classification using high order statistical features, International Conference on Forest Fire Research ICFFR, Coimbra, Portugal, November, 2022. https://doi.org/10.14195/978-989-26-2298-9_31

National Conferences

  1. B. Amaral, A. Bernardino and C. Barata. “Fire and Smoke Detection in Aerial Images”. In Proceedings of the 26th Portuguese Conference on Pattern Recognition. 2020. https://recpad2020.uevora.pt/wp-content/uploads/2020/11/proceedings_recpad2020.pdf
  2. G. Perrolas, A. Bernardino and R. Ribeiro. “Fire and Smoke Detection using CNN’s trained with Fully Supervised methods and Search by Quad-Tree”. 26th Portuguese Conference on Pattern Recognition. 2020. https://recpad2020.uevora.pt/wp-content/uploads/2020/11/proceedings_recpad2020.pdf
  3. B. Santana, A. Bernardino and R. Ribeiro. “Direct Georeferecing of Fire Front Aerial Images using Iterative Ray-Tracing and a Bearings-Range Extended Kalman Filter”. 26th Portuguese Conference on Pattern Recognition. 2020. https://recpad2020.uevora.pt/wp-content/uploads/2020/11/proceedings_recpad2020.pdf

Theses

  1. Direct Georeferencing of Fire Front Aerial Images using Iterative Ray-Tracing and a Bearings-Range Extended Kalman Filter. Bernardo Maria Gonçalves Santana, MSc Thesis, IST 2021. https://fenix.tecnico.ulisboa.pt/cursos/meec/dissertacao/846778572212614
  2. Fire and smoke detection using Fully Supervised training Methods and search by Quadtree. Gonçalo de Carvalho Rodrigues Callet Perrolas, MSc Thesis, IST, 2021. https://fenix.tecnico.ulisboa.pt/cursos/meec/dissertacao/846778572212458
  3. Fire and Smoke detection with weakly supervised methods. Bernardo Filipe Morais Amaral, MSc Thesis, IST 2021. https://fenix.tecnico.ulisboa.pt/cursos/meec/dissertacao/846778572213413
  4. Semi-supervised Semantic Segmentation of Smoke and Fire from Airborne Images with Generative Adversarial Networks to support Firefighting Actions. Lisa Kuhlmann, MSc Thesis, HTW Berlim, 2021. omni.isr.tecnico.ulisboa.pt/~alex/firefront/Lisa_Kuhlmann_Semi_Supervised_Smoke_Fire_Segmentation.pdf
  5. Detecção de incêndios florestais através da aprendizagem auto-supervisionada. Sara Alexandra Curado Fernandes. MSc Thesis, IST, 2021. https://fenix.tecnico.ulisboa.pt/cursos/meec/dissertacao/1691203502344336
  6. Learning Performance Models of Distributed Computer Vision Methods for Decision Making in Detection and Tracking Algorithms in UAVs. João Diogo Patrão Silva Correia, MSc Thesis, IST 2021. https://fenix.tecnico.ulisboa.pt/cursos/meec/dissertacao/1691203502344399
  7. Georeferencing of Fire Front Aerial Images using Structure from motion and Iterative Closest Point. Francisco Goulão Sargento, MSc Thesis, IST, 2021. https://fenix.tecnico.ulisboa.pt/cursos/meaer/dissertacao/1691203502344341
  8. Development of high-resolution maps of vegetation cover to support land planning and grazing management in fire prone landscapes. Bianka Trencanova, MSc Thesis, IST 2021. https://fenix.tecnico.ulisboa.pt/cursos/mege/dissertacao/283828618790519
  9. Wildfire Detection based on Image Movement Analysis. Tiago Filipe da Costa Silvério, MSc Thesis, IST 2021. https://fenix.tecnico.ulisboa.pt/cursos/meec/dissertacao/1691203502344358
  10. (2022) Fire and Smoke Detection using Active Learning Methods, Tiago Ruivo Marto, IST, 2022.