publicações selecionadas Irrigated rice crop identification in Southern Brazil using convolutional neural networks and Sentinel-1 time series Deep semantic segmentation of mangroves in Brazil combining spatial, temporal, and polarization data from Sentinel-1 time series Deep-water oil-spill monitoring and recurrence analysis in the Brazilian territory using Sentinel-1 time series and deep learning Deep Semantic Segmentation of Center Pivot Irrigation Systems from Remotely Sensed Data Dealing With Clouds and Seasonal Changes for Center Pivot Irrigation Systems Detection Using Instance Segmentation in Sentinel-2 Time Series Multispectral panoptic segmentation: Exploring the beach setting with worldview-3 imagery Deep Semantic Segmentation for Detecting Eucalyptus Planted Forests in the Brazilian Territory Using Sentinel-2 Imagery Performance Analysis of Deep Convolutional Autoencoders with Different Patch Sizes for Change Detection from Burnt Areas Remote Sensing for Monitoring Photovoltaic Solar Plants in Brazil Using Deep Semantic Segmentation Deep learning & remote sensing: pushing the frontiers in image sementation Bounding Box-Free Instance Segmentation Using Semi-Supervised Iterative Learning for Vehicle~Detection Estimating the Optimal Threshold for Accuracy Assessment of the Global Ecosystem Dynamics Investigation (GEDI) Data in a Gentle Relief Urban Area Prediction of secondary testosterone deficiency using machine learning: A comparative analysis of ensemble and base classifiers, probability calibration, and sampling strategies in a slightly imbalanced dataset Panoptic Segmentation Meets Remote Sensing Rice Crop Detection Using LSTM, Bi-LSTM, and Machine Learning Models from Sentinel-1 Time Series Instance segmentation of center pivot irrigation systems using multi-temporal SENTINEL-1 SAR images Relationship between Land Property Security and Brazilian Amazon Deforestation in the Mato Grosso State during the Period 2013-2018 Rethinking Panoptic Segmentation in Remote Sensing: A Hybrid Approach Using Semantic Segmentation and non-Learning Methods MP63-03-MACHINE LEARNING AND NOCTURIA: A BETTER UNDERSTANDING OF RISK FACTORS A Data-Centric Approach for Wind Plant Instance-Level Segmentation Using Semantic Segmentation and GIS Comparing Machine and Deep Learning Methods for the Phenology-Based Classification of Land Cover Types in the Amazon Biome Ecosystem Using Sentinel-1 Time Series Instance Segmentation for Governmental Inspection of Small Touristic Infrastructure in Beach Zones Using Multispectral High-Resolution WorldView-3 Imagery Instance Segmentation for Large, Multi-Channel Remote Sensing Imagery Using Mask-RCNN and a Mosaicking Approach
