activity
20202023
most citedSelf-Supervised Keypoint Discovery in Behavioral Videos

8 citations · 13 across the 5 of their papers we have counts for

collaborators

5 papers

physics.flu-dyn20231 cited

Visual anemometry: physics-informed inference of wind for renewable energy, urban sustainability, and environmental science

John O. Dabiri, Michael F. Howland, Matthew K. Fu +1

Accurate measurements of atmospheric flows at meter-scale resolution are essential for a broad range of sustainability applications, including optimal design of wind and solar farm…

physics.flu-dyn2023

Persistent Laminar Flow at Reynolds Numbers Exceeding 100,000

John O. Dabiri, Nina Mohebbi, Matthew K. Fu

Accurate prediction of the transition from laminar flow to turbulence remains an unresolved challenge despite its importance for understanding a variety of environmental, biologica…

physics.flu-dyn2022

Physical constraints on visual anemometry using vegetation displacement statistics

Roni H. Goldshmid, John O. Dabiri

Visual anemometry (VA) leverages observations of fluid-structure interactions to infer incident flow characteristics. Recent work has demonstrated the concept of VA using both data…

cs.CV20218 cited

Self-Supervised Keypoint Discovery in Behavioral Videos

Jennifer J. Sun, Serim Ryou, Roni Goldshmid +6

We propose a method for learning the posture and structure of agents from unlabelled behavioral videos. Starting from the observation that behaving agents are generally the main so…

physics.flu-dyn20204 cited

Influence of atmospheric conditions on the power production of utility-scale wind turbines in yaw misalignment

Michael F. Howland, Carlos Moral Gonzalez, Juan Jose Pena Martinez +5

The intentional yaw misalignment of leading, upwind turbines in a wind farm, termed wake steering, has demonstrated potential as a collective control approach for wind farm power m…