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Rodrigo Minetto | Bogdan Tomoyuki Nassu | Andr'e Minoro Fusioka | Gabriel Henrique de Almeida Pereira | G. Pereira | R. Minetto | B. Nassu
[1] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[2] Valero Laparra,et al. Transferring deep learning models for cloud detection between Landsat-8 and Proba-V , 2020 .
[3] Chen Chen,et al. SmokeNet: Satellite Smoke Scene Detection Using Convolutional Neural Network with Spatial and Channel-Wise Attention , 2019, Remote. Sens..
[4] R. Wright,et al. HOTMAP: Global hot target detection at moderate spatial resolution , 2016 .
[5] Ronan Collobert,et al. Learning to Segment Object Candidates , 2015, NIPS.
[6] Lorenzo Busetto,et al. PhenoRice: A method for automatic extraction of spatio-temporal information on rice crops using satellite data time series , 2017 .
[7] Yoram J. Kaufman,et al. An Enhanced Contextual Fire Detection Algorithm for MODIS , 2003 .
[8] Pietro Perona,et al. Microsoft COCO: Common Objects in Context , 2014, ECCV.
[9] Isabel F. Trigo,et al. A deep learning approach for mapping and dating burned areas using temporal sequences of satellite images , 2020 .
[10] W. Schroeder,et al. Active fire detection using Landsat-8/OLI data , 2016 .
[11] Steven C. H. Hoi,et al. Deep Learning for Image Super-Resolution: A Survey , 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[12] Santiago Monedero,et al. Assessing and reinitializing wildland fire simulations through satellite active fire data. , 2019, Journal of environmental management.
[13] Joanne V. Hall,et al. A systematic evaluation of influence of image selection process on remote sensing-based burn severity indices in North American boreal forest and tundra ecosystems , 2020 .
[14] N. Koutsias,et al. Historical background and current developments for mapping burned area from satellite Earth observation , 2019, Remote Sensing of Environment.
[15] José García Rodríguez,et al. A survey on deep learning techniques for image and video semantic segmentation , 2018, Appl. Soft Comput..
[16] Mercedes Eugenia Paoletti,et al. Deep learning classifiers for hyperspectral imaging: A review , 2019 .
[17] M. Wulder,et al. Near Real-Time Wildfire Progression Monitoring with Sentinel-1 SAR Time Series and Deep Learning , 2020, Scientific Reports.
[18] Hongzhang Xu,et al. Deep learning in environmental remote sensing: Achievements and challenges , 2020, Remote Sensing of Environment.
[19] Jitendra Kumar,et al. Wildfire Mapping in Interior Alaska Using Deep Neural Networks on Imbalanced Datasets , 2018, 2018 IEEE International Conference on Data Mining Workshops (ICDMW).
[20] Jannik Fritsch,et al. A new performance measure and evaluation benchmark for road detection algorithms , 2013, 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013).
[21] Antonio Iodice,et al. A CNN-based Super-resolution Technique for Active Fire Detection on Sentinel-2 Data , 2019, 2019 PhotonIcs & Electromagnetics Research Symposium - Spring (PIERS-Spring).
[22] Xiao Xiang Zhu,et al. Deep learning in remote sensing: a review , 2017, ArXiv.
[23] Beth Sundheim,et al. MUC-5 Evaluation Metrics , 1993, MUC.
[24] C. Justice,et al. The collection 6 MODIS active fire detection algorithm and fire products , 2016, Remote sensing of environment.
[25] Erich Franz Stocker,et al. Seasonal, intraseasonal, and interannual variability of global land fires and their effects on atmospheric aerosol distribution , 2002 .
[26] Tao Lei,et al. A review of Convolutional-Neural-Network-based action recognition , 2019, Pattern Recognit. Lett..
[27] Lonesome Malambo,et al. Automated training sample definition for seasonal burned area mapping , 2020 .
[28] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[29] Yecheng Lyu,et al. Road Segmentation using CNN and Distributed LSTM , 2018, 2019 IEEE International Symposium on Circuits and Systems (ISCAS).
[30] Luc Van Gool,et al. The Pascal Visual Object Classes (VOC) Challenge , 2010, International Journal of Computer Vision.
[31] Rodrigo Minetto,et al. Hydra: An Ensemble of Convolutional Neural Networks for Geospatial Land Classification , 2018, IEEE Transactions on Geoscience and Remote Sensing.
[32] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[33] Bram van Ginneken,et al. A survey on deep learning in medical image analysis , 2017, Medical Image Anal..
[34] A. Edwards,et al. Sensitivity of the MODIS fire detection algorithm (MOD14) in the savanna region of the Northern Territory, Australia , 2013 .
[35] C. Justice,et al. Potential global fire monitoring from EOS‐MODIS , 1998 .
[36] Dario Augusto Borges Oliveira,et al. Synthesis of Multispectral Optical Images From SAR/Optical Multitemporal Data Using Conditional Generative Adversarial Networks , 2019, IEEE Geoscience and Remote Sensing Letters.
[37] Xueliang Zhang,et al. Deep learning in remote sensing applications: A meta-analysis and review , 2019, ISPRS Journal of Photogrammetry and Remote Sensing.
[38] Martha C. Anderson,et al. Landsat-8: Science and Product Vision for Terrestrial Global Change Research , 2014 .
[39] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[40] W. Schroeder,et al. The New VIIRS 375 m active fire detection data product: Algorithm description and initial assessment , 2014 .
[41] C. Justice,et al. Validation of the MODIS active fire product over Southern Africa with ASTER data , 2005 .
[42] C. Portillo-Quintero,et al. Monitoring deforestation with MODIS Active Fires in Neotropical dry forests: An analysis of local-scale assessments in Mexico, Brazil and Bolivia , 2013 .
[43] T. H. Haar,et al. Forest fire monitoring using NOAA satellite AVHRR , 1986 .
[44] Xiaojin Zhu,et al. Semi-Supervised Learning , 2010, Encyclopedia of Machine Learning.
[45] David Bergström,et al. Hyperspectral image analysis using deep learning — A review , 2016, 2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA).
[46] Elbert E. N. Macau,et al. Global fire season severity analysis and forecasting , 2019, Comput. Geosci..
[47] David P. Roy,et al. Global operational land imager Landsat-8 reflectance-based active fire detection algorithm , 2018, Int. J. Digit. Earth.
[48] B. Holben,et al. Satellite detection of tropical burning in Brazil , 1987 .
[49] Thomas F. Lee,et al. Improved Detection of Hotspots using the AVHRR 3.7-um Channel , 1990 .