114 citations · 276 across the 15 of their papers we have counts for
10 papers · 1 filter
Spatial Context Awareness for Unsupervised Change Detection in Optical Satellite Images
Lukas Kondmann, Aysim Toker, Sudipan Saha +3
Detecting changes on the ground in multitemporal Earth observation data is one of the key problems in remote sensing. In this paper, we introduce Sibling Regression for Optical Cha…
Reiterative Domain Aware Multi-Target Adaptation
Sudipan Saha, Shan Zhao, Nasrullah Sheikh +1
Most domain adaptation methods focus on single-source-single-target adaptation settings. Multi-target domain adaptation is a powerful extension in which a single classifier is lear…
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…
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…
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…
Deep Reinforcement Learning for Band Selection in Hyperspectral Image Classification
Lichao Mou, Sudipan Saha, Yuansheng Hua +3
Band selection refers to the process of choosing the most relevant bands in a hyperspectral image. By selecting a limited number of optimal bands, we aim at speeding up model train…
Self-Supervised Multisensor Change Detection
Sudipan Saha, Patrick Ebel, Xiao Xiang Zhu
Most change detection methods assume that pre-change and post-change images are acquired by the same sensor. However, in many real-life scenarios, e.g., natural disaster, it is mor…
Towards Bridging the gap between Empirical and Certified Robustness against Adversarial Examples
Jay Nandy, Sudipan Saha, Wynne Hsu +2
The current state-of-the-art defense methods against adversarial examples typically focus on improving either empirical or certified robustness. Among them, adversarially trained (…
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…