8 citations · 26 across the 11 of their papers we have counts for
6 papers · 1 filter
Curator: Creating Large-Scale Curated Labelled Datasets using Self-Supervised Learning
Tarun Narayanan, Ajay Krishnan, Anirudh Koul +1
Applying Machine learning to domains like Earth Sciences is impeded by the lack of labeled data, despite a large corpus of raw data available in such domains. For instance, trainin…
CELESTIAL: Classification Enabled via Labelless Embeddings with Self-supervised Telescope Image Analysis Learning
Suhas Kotha, Anirudh Koul, Siddha Ganju +1
A common class of problems in remote sensing is scene classification, a fundamentally important task for natural hazards identification, geographic image retrieval, and environment…
Scalable Reverse Image Search Engine for NASAWorldview
Abhigya Sodani, Michael Levy, Anirudh Koul +2
Researchers often spend weeks sifting through decades of unlabeled satellite imagery(on NASA Worldview) in order to develop datasets on which they can start conducting research. We…
Reducing Effects of Swath Gaps on Unsupervised Machine Learning Models for NASA MODIS Instruments
Sarah Chen, Esther Cao, Anirudh Koul +3
Due to the nature of their pathways, NASA Terra and NASA Aqua satellites capture imagery containing swath gaps, which are areas of no data. Swath gaps can overlap the region of int…
Scalable Data Balancing for Unlabeled Satellite Imagery
Deep Patel, Erin Gao, Anirudh Koul +2
Data imbalance is a ubiquitous problem in machine learning. In large scale collected and annotated datasets, data imbalance is either mitigated manually by undersampling frequent c…
SpaceML: Distributed Open-source Research with Citizen Scientists for the Advancement of Space Technology for NASA
Anirudh Koul, Siddha Ganju, Meher Kasam +1
Traditionally, academic labs conduct open-ended research with the primary focus on discoveries with long-term value, rather than direct products that can be deployed in the real wo…