16 citations · 94 across the 59 of their papers we have counts for
6 papers · 1 filter
Analyzing Worldwide Social Distancing through Large-Scale Computer Vision
Isha Ghodgaonkar, Subhankar Chakraborty, Vishnu Banna +15
In order to contain the COVID-19 pandemic, countries around the world have introduced social distancing guidelines as public health interventions to reduce the spread of the diseas…
Low-Power Object Counting with Hierarchical Neural Networks
Abhinav Goel, Caleb Tung, Sara Aghajanzadeh +4
Deep Neural Networks (DNNs) can achieve state-of-the-art accuracy in many computer vision tasks, such as object counting. Object counting takes two inputs: an image and an object q…
Observing Responses to the COVID-19 Pandemic using Worldwide Network Cameras
Isha Ghodgaonkar, Abhinav Goel, Fischer Bordwell +18
COVID-19 has resulted in a worldwide pandemic, leading to "lockdown" policies and social distancing. The pandemic has profoundly changed the world. Traditional methods for observin…
VoltKey: Using Power Line Noise for Zero-Involvement Pairing and Authentication (Demo Abstract)
Jack West, Tien VoNguyen, Isaac Ahlgren +3
We present VoltKey, a method that transparently generates secret keys for colocated devices, leveraging spatiotemporally unique noise contexts observed in commercial power line inf…
FLIC: A Distributed Fog Cache for City-Scale Applications
Jack West, Neil Kingensmith, George K. Thiruvathukal
We present FLIC, a distributed software data caching framework for fogs that reduces network traffic and latency. FLICis targeted toward city-scale deployments of cooperative IoT d…
A Survey of Methods for Low-Power Deep Learning and Computer Vision
Abhinav Goel, Caleb Tung, Yung-Hsiang Lu +1
Deep neural networks (DNNs) are successful in many computer vision tasks. However, the most accurate DNNs require millions of parameters and operations, making them energy, computa…