189 citations · 243 across the 21 of their papers we have counts for
11 papers · 1 filter
A Generalization of Continuous Relaxation in Structured Pruning
Brad Larson, Bishal Upadhyaya, Luke McDermott +1
Deep learning harnesses massive parallel floating-point processing to train and evaluate large neural networks. Trends indicate that deeper and larger neural networks with an incre…
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…
Deep learning based landslide density estimation on SAR data for rapid response
Vanessa Boehm, Wei Ji Leong, Ragini Bal Mahesh +5
This work aims to produce landslide density estimates using Synthetic Aperture Radar (SAR) satellite imageries to prioritise emergency resources for rapid response. We use the Unit…
SAR-based landslide classification pretraining leads to better segmentation
Vanessa Böhm, Wei Ji Leong, Ragini Bal Mahesh +5
Rapid assessment after a natural disaster is key for prioritizing emergency resources. In the case of landslides, rapid assessment involves determining the extent of the area affec…
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…
Flood Segmentation on Sentinel-1 SAR Imagery with Semi-Supervised Learning
Sayak Paul, Siddha Ganju
Floods wreak havoc throughout the world, causing billions of dollars in damages, and uprooting communities, ecosystems and economies. The NASA Impact Flood Detection competition ta…
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…
What's in a Question: Using Visual Questions as a Form of Supervision
Siddha Ganju, Olga Russakovsky, Abhinav Gupta
Collecting fully annotated image datasets is challenging and expensive. Many types of weak supervision have been explored: weak manual annotations, web search results, temporal con…