Driven by rapid climate change, the frequency and intensity of flood eve...
Label-efficient and reliable semantic segmentation is essential for many...
Semi-supervised semantic segmentation learns a model for classifying pix...
Mixup provides interpolated training samples and allows the model to obt...
Future frame prediction has been approached through two primary methods:...
Geostationary satellite imagery has applications in climate and weather
...
For change detection in remote sensing, constructing a training dataset ...
Deep learning-based weather prediction models have advanced significantl...
Traditional weather forecasting relies on domain expertise and
computati...
The Visual Domain Adaptation(VisDA) 2022 Challenge calls for an unsuperv...
In this paper, we introduce source domain subset sampling (SDSS) as a ne...
To train the change detector, bi-temporal images taken at different time...
Labeling a large set of data is expensive. Active learning aims to tackl...
Deep convolutional neural networks (CNNs) have shown state-of-the-art
pe...
We propose Sequential Feature Filtering Classifier (FFC), a simple but
e...