15 citations · 34 across the 6 of their papers we have counts for
7 papers
Efficient Computer Vision on Edge Devices with Pipeline-Parallel Hierarchical Neural Networks
Abhinav Goel, Caleb Tung, Xiao Hu +3
Computer vision on low-power edge devices enables applications including search-and-rescue and security. State-of-the-art computer vision algorithms, such as Deep Neural Networks (…
Low-Power Multi-Camera Object Re-Identification using Hierarchical Neural Networks
Abhinav Goel, Caleb Tung, Xiao Hu +4
Low-power computer vision on embedded devices has many applications. This paper describes a low-power technique for the object re-identification (reID) problem: matching a query im…
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…
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…