most citedGenerative modeling of spatio-temporal weather patterns with extreme event conditioning

9 citations · 10 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV2021

Segmentation of VHR EO Images using Unsupervised Learning

Sudipan Saha, Lichao Mou, Muhammad Shahzad +1

Semantic segmentation is a crucial step in many Earth observation tasks. Large quantity of pixel-level annotation is required to train deep networks for semantic segmentation. Eart…

cs.CV20219 cited

Generative modeling of spatio-temporal weather patterns with extreme event conditioning

Konstantin Klemmer, Sudipan Saha, Matthias Kahl +2

Deep generative models are increasingly used to gain insights in the geospatial data domain, e.g., for climate data. However, most existing approaches work with temporal snapshots…

cs.LG2021

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…

cs.LG20211 cited

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…

eess.IV2021

Ultrasound Image Classification using ACGAN with Small Training Dataset

Sudipan Saha, Nasrullah Sheikh

B-mode ultrasound imaging is a popular medical imaging technique. Like other image processing tasks, deep learning has been used for analysis of B-mode ultrasound images in the las…

cs.LG2020

Federated Transfer Learning: concept and applications

Sudipan Saha, Tahir Ahmad

Development of Artificial Intelligence (AI) is inherently tied to the development of data. However, in most industries data exists in form of isolated islands, with limited scope o…