paper-with-me

Flood extent forecasting

1개 벤치마크 · 논문 5편 · 이 태스크의 논문 보기 →

Benchmarks

Most implemented

Papers

Off to new Shores: A Dataset & Benchmark for (near-)coastal Flood Inundation Forecasting

2024-09-27 · Brandon Victor, Mathilde Letard, Peter Naylor, Karim Douch 외

Floods are among the most common and devastating natural hazards, imposing immense costs on our society and economy due to their disastrous consequences. Recent progress in weather prediction and spaceborne flood mapping…

Flood extent forecasting

MaxViT-UNet: Multi-Axis Attention for Medical Image Segmentation

2023-05-15 · Abdul Rehman Khan, Asifullah Khan

Since their emergence, Convolutional Neural Networks (CNNs) have made significant strides in medical image analysis. However, the local nature of the convolution operator may pose a limitation for capturing global and lo…

DecoderFlood extent forecastingImage SegmentationInductive Bias+4

Next Day Wildfire Spread: A Machine Learning Data Set to Predict Wildfire Spreading from Remote-Sensing Data

2021-12-04 · Fantine Huot, R. Lily Hu, Nita Goyal, Tharun Sankar 외

Predicting wildfire spread is critical for land management and disaster preparedness. To this end, we present `Next Day Wildfire Spread,' a curated, large-scale, multivariate data set of historical wildfires aggregating …

BIG-bench Machine LearningEarth ObservationFlood extent forecastingManagement

Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks

2021-07-16 · ICCV 2021 10 · Vivien Sainte Fare Garnot, Loic Landrieu

Unprecedented access to multi-temporal satellite imagery has opened new perspectives for a variety of Earth observation tasks. Among them, pixel-precise panoptic segmentation of agricultural parcels has major economic an…

Cloud RemovalEarth ObservationFlood extent forecastingPanoptic Segmentation+5

Semantic segmentation of crop type in Africa: A novel dataset and analysis of deep learning methods

2019-06-01 · CVPR 2019 6 · Rose Rustowicz, Robin Cheong, Lijing Wang, Stefano Ermon 외

Automatic, accurate crop type maps can provide unprecedented information for understanding food systems, especially in developing countries where ground surveys are infrequent. However, little work has applied existing m…

Crop Type MappingFlood extent forecastingSemantic Segmentation