15 citations · 49 across the 15 of their papers we have counts for
16 papers
An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry
Wenxin Jiang, Nicholas Synovic, Matt Hyatt +5
Deep Neural Networks (DNNs) are being adopted as components in software systems. Creating and specializing DNNs from scratch has grown increasingly difficult as state-of-the-art ar…
Why Accuracy Is Not Enough: The Need for Consistency in Object Detection
Caleb Tung, Abhinav Goel, Fischer Bordwell +4
Object detectors are vital to many modern computer vision applications. However, even state-of-the-art object detectors are not perfect. On two images that look similar to human ey…
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 (…
An Experience Report on Machine Learning Reproducibility: Guidance for Practitioners and TensorFlow Model Garden Contributors
Vishnu Banna, Akhil Chinnakotla, Zhengxin Yan +7
Machine learning techniques are becoming a fundamental tool for scientific and engineering progress. These techniques are applied in contexts as diverse as astronomy and spam filte…
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…
Automated Discovery of Real-Time Network Camera Data From Heterogeneous Web Pages
Ryan Dailey, Aniesh Chawla, Andrew Liu +5
Reduction in the cost of Network Cameras along with a rise in connectivity enables entities all around the world to deploy vast arrays of camera networks. Network cameras offer rea…
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…
Low-Power Computer Vision: Status, Challenges, Opportunities
Sergei Alyamkin, Matthew Ardi, Alexander C. Berg +41
Computer vision has achieved impressive progress in recent years. Meanwhile, mobile phones have become the primary computing platforms for millions of people. In addition to mobile…
See the World through Network Cameras
Yung-Hsiang Lu, George K. Thiruvathukal, Ahmed S. Kaseb +7
Millions of network cameras have been deployed worldwide. Real-time data from many network cameras can offer instant views of multiple locations with applications in public safety,…
Low Power Inference for On-Device Visual Recognition with a Quantization-Friendly Solution
Chen Feng, Tao Sheng, Zhiyu Liang +9
The IEEE Low-Power Image Recognition Challenge (LPIRC) is an annual competition started in 2015 that encourages joint hardware and software solutions for computer vision systems wi…
Cross-referencing Social Media and Public Surveillance Camera Data for Disaster Response
Chittayong Surakitbanharn, Calvin Yau, Guizhen Wang +7
Physical media (like surveillance cameras) and social media (like Instagram and Twitter) may both be useful in attaining on-the-ground information during an emergency or disaster s…
2018 Low-Power Image Recognition Challenge
Sergei Alyamkin, Matthew Ardi, Achille Brighton +38
The Low-Power Image Recognition Challenge (LPIRC, https://rebootingcomputing.ieee.org/lpirc) is an annual competition started in 2015. The competition identifies the best technolog…
Analyzing Real-Time Multimedia Content From Network Cameras Using CPUs and GPUs in the Cloud
Ahmed S. Kaseb, Bo Fu, Anup Mohan +3
Millions of network cameras are streaming real-time multimedia content (images or videos) for various environments (e.g., highways and malls) and can be used for a variety of appli…