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Found 5 papers, 0 papers with code
Analyzing Worldwide Social Distancing through Large-Scale Computer Vision
This research team has created methods that can discover thousands of network cameras worldwide, retrieve data from the cameras, analyze the data, and report the sizes of crowds as different countries issued and lifted restrictions (also called ''lockdown'').
Geovisual Analytics and Interactive Machine Learning for Situational Awareness
The first responder community has traditionally relied on calls from the public, officially-provided geographic information and maps for coordinating actions on the ground.
City-level Geolocation of Tweets for Real-time Visual Analytics
In this paper, we adapt, improve, and evaluate a state-of-the-art deep learning model for city-level geolocation prediction, and integrate it with a visual analytics system tailored for real-time situational awareness.
Interactive Learning for Identifying Relevant Tweets to Support Real-time Situational Awareness
We present a novel interactive learning framework to improve the classification process in which the user iteratively corrects the relevancy of tweets in real-time to train the classification model on-the-fly for immediate predictive improvements.
Manifold: A Model-Agnostic Framework for Interpretation and Diagnosis of Machine Learning Models
We present Manifold, a framework that utilizes visual analysis techniques to support interpretation, debugging, and comparison of machine learning models in a more transparent and interactive manner.
