activity
20202022
most citedMulti-source Domain Adaptation in the Deep Learning Era: A Systematic Survey

73 citations · 85 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CV20224 cited

Prior Knowledge-Guided Attention in Self-Supervised Vision Transformers

Kevin Miao, Akash Gokul, Raghav Singh +5

Recent trends in self-supervised representation learning have focused on removing inductive biases from training pipelines. However, inductive biases can be useful in settings when…

cs.LG2022

SunCast: Solar Irradiance Nowcasting from Geosynchronous Satellite Data

Dhileeban Kumaresan, Richard Wang, Ernesto Martinez +4

When cloud layers cover photovoltaic (PV) panels, the amount of power the panels produce fluctuates rapidly. Therefore, to maintain enough energy on a power grid to match demand, u…

cs.CV20222 cited

HyperionSolarNet: Solar Panel Detection from Aerial Images

Poonam Parhar, Ryan Sawasaki, Alberto Todeschini +4

With the effects of global climate change impacting the world, collective efforts are needed to reduce greenhouse gas emissions. The energy sector is the single largest contributor…

cs.CV20212 cited

Multi-source Few-shot Domain Adaptation

Xiangyu Yue, Zangwei Zheng, Colorado Reed +3

Multi-source Domain Adaptation (MDA) aims to transfer predictive models from multiple, fully-labeled source domains to an unlabeled target domain. However, in many applications, re…

cs.CV20214 cited

Self-supervised Contrastive Learning for Irrigation Detection in Satellite Imagery

Chitra Agastya, Sirak Ghebremusse, Ian Anderson +3

Climate change has caused reductions in river runoffs and aquifer recharge resulting in an increasingly unsustainable crop water demand from reduced freshwater availability. Achiev…

cs.CV2021

Self-Supervised Pretraining Improves Self-Supervised Pretraining

Colorado J. Reed, Xiangyu Yue, Ani Nrusimha +9

While self-supervised pretraining has proven beneficial for many computer vision tasks, it requires expensive and lengthy computation, large amounts of data, and is sensitive to da…