3.2k citations · 10k across the 87 of their papers we have counts for
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Exploring Geometric Deep Learning For Precipitation Nowcasting
Shan Zhao, Sudipan Saha, Zhitong Xiong +2
Precipitation nowcasting (up to a few hours) remains a challenge due to the highly complex local interactions that need to be captured accurately. Convolutional Neural Networks rel…
Landscape of Neural Architecture Search across sensors: how much do they differ ?
Kalifou René Traoré, Andrés Camero, Xiao Xiang Zhu
With the rapid rise of neural architecture search, the ability to understand its complexity from the perspective of a search algorithm is desirable. Recently, Traoré et al. have pr…
A Survey of Uncertainty in Deep Neural Networks
Jakob Gawlikowski, Cedrique Rovile Njieutcheu Tassi, Mohsin Ali +11
Due to their increasing spread, confidence in neural network predictions became more and more important. However, basic neural networks do not deliver certainty estimates or suffer…
Trusting small training dataset for supervised change detection
Sudipan Saha, Biplab Banerjee, Xiao Xiang Zhu
Deep learning (DL) based supervised change detection (CD) models require large labeled training data. Due to the difficulty of collecting labeled multi-temporal data, unsupervised…
Out-of-distribution detection in satellite image classification
Jakob Gawlikowski, Sudipan Saha, Anna Kruspe +1
In satellite image analysis, distributional mismatch between the training and test data may arise due to several reasons, including unseen classes in the test data and differences…
Fusion of Heterogeneous Earth Observation Data for the Classification of Local Climate Zones
Guichen Zhang, Pedram Ghamisi, Xiao Xiang Zhu
This paper proposes a novel framework for fusing multi-temporal, multispectral satellite images and OpenStreetMap (OSM) data for the classification of local climate zones (LCZs). F…