6 citations · 18 across the 4 of their papers we have counts for
4 papers
SeMAnD: Self-Supervised Anomaly Detection in Multimodal Geospatial Datasets
Daria Reshetova, Swetava Ganguli, C. V. Krishnakumar Iyer +1
We propose a Self-supervised Anomaly Detection technique, called SeMAnD, to detect geometric anomalies in Multimodal geospatial datasets. Geospatial data comprises of acquired and…
Scalable Self-Supervised Representation Learning from Spatiotemporal Motion Trajectories for Multimodal Computer Vision
Swetava Ganguli, C. V. Krishnakumar Iyer, Vipul Pandey
Self-supervised representation learning techniques utilize large datasets without semantic annotations to learn meaningful, universal features that can be conveniently transferred…
Reachability Embeddings: Scalable Self-Supervised Representation Learning from Mobility Trajectories for Multimodal Geospatial Computer Vision
Swetava Ganguli, C. V. Krishnakumar Iyer, Vipul Pandey
Self-supervised representation learning techniques utilize large datasets without semantic annotations to learn meaningful, universal features that can be conveniently transferred…
Trinity: A No-Code AI platform for complex spatial datasets
C. V. Krishnakumar Iyer, Feili Hou, Henry Wang +4
We present a no-code Artificial Intelligence (AI) platform called Trinity with the main design goal of enabling both machine learning researchers and non-technical geospatial domai…