8 citations · 14 across the 7 of their papers we have counts for
7 papers
Methane Detection On Board Satellites from Unorthorectified Imagery
Luca Marini, Maggie Chen, Hala Lamdouar +3
As a potent greenhouse gas, methane is a major driver of climate change. Its effective mitigation relies on timely detection. Conventional detection methods rely on orthorectificat…
HiSAXy: A fast methodology for solar wind structure identification in millions of time series
Hala Lamdouar, Sairam Sundaresan, Anna Jungbluth +8
We present a hybridized unsupervised clustering algorithm Hisaxy as a novel way to identify frequently occurring magnetic structures embedded in the interplanetary magnetic field (…
CIPHER: Scalable Time Series Analysis for Physical Sciences with Application to Solar Wind Phenomena
Jasmine R. Kobayashi, Daniela Martin, Valmir P Moraes Filho +12
Labeling or classifying time series is a persistent challenge in the physical sciences, where expert annotations are scarce, costly, and often inconsistent. Yet robust labeling is…
The Making and Breaking of Camouflage
Hala Lamdouar, Weidi Xie, Andrew Zisserman
Not all camouflages are equally effective, as even a partially visible contour or a slight color difference can make the animal stand out and break its camouflage. In this paper, w…
Deep-SWIM: A few-shot learning approach to classify Solar WInd Magnetic field structures
Hala Lamdouar, Sairam Sundaresan, Anna Jungbluth +9
The solar wind consists of charged particles ejected from the Sun into interplanetary space and towards Earth. Understanding the magnetic field of the solar wind is crucial for pre…
Self-supervised Video Object Segmentation by Motion Grouping
Charig Yang, Hala Lamdouar, Erika Lu +2
Animals have evolved highly functional visual systems to understand motion, assisting perception even under complex environments. In this paper, we work towards developing a comput…
Betrayed by Motion: Camouflaged Object Discovery via Motion Segmentation
Hala Lamdouar, Charig Yang, Weidi Xie +1
The objective of this paper is to design a computational architecture that discovers camouflaged objects in videos, specifically by exploiting motion information to perform object…