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Analyzing Worldwide Social Distancing through Large-Scale Computer Vision
In order to contain the COVID-19 pandemic, countries around the world ha...
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Low-Power Object Counting with Hierarchical Neural Networks
Deep Neural Networks (DNNs) can achieve state-of-the-art accuracy in man...
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Observing Responses to the COVID-19 Pandemic using Worldwide Network Cameras
COVID-19 has resulted in a worldwide pandemic, leading to "lockdown" pol...
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A Survey of Methods for Low-Power Deep Learning and Computer Vision
Deep neural networks (DNNs) are successful in many computer vision tasks...
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Low-Power Computer Vision: Status, Challenges, Opportunities
Computer vision has achieved impressive progress in recent years. Meanwh...
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See the World through Network Cameras
Millions of network cameras have been deployed worldwide. Real-time data...
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Low Power Inference for On-Device Visual Recognition with a Quantization-Friendly Solution
The IEEE Low-Power Image Recognition Challenge (LPIRC) is an annual comp...
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Cross-referencing Social Media and Public Surveillance Camera Data for Disaster Response
Physical media (like surveillance cameras) and social media (like Instag...
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Cloud Resource Optimization for Processing Multiple Streams of Visual Data
Hundreds of millions of network cameras have been installed throughout t...
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Large-Scale Object Detection of Images from Network Cameras in Variable Ambient Lighting Conditions
Computer vision relies on labeled datasets for training and evaluation i...
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2018 Low-Power Image Recognition Challenge
The Low-Power Image Recognition Challenge (LPIRC, https://rebootingcompu...
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Analyzing Real-Time Multimedia Content From Network Cameras: Using CPUs and GPUs in the Cloud
Millions of network cameras are streaming real-time multimedia content (...
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