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Found 6 papers, 3 papers with code
Considerations, Good Practices, Risks and Pitfalls in Developing AI Solutions Against COVID-19
The COVID-19 pandemic has been a major challenge to humanity, with 12. 7 million confirmed cases as of July 13th, 2020 [1].
Mapping the Landscape of Artificial Intelligence Applications against COVID-19
COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, which has reported over 18 million confirmed cases as of August 5, 2020.
Using neural networks for efficient evaluation of high multiplicity scattering amplitudes
Precision theoretical predictions for high multiplicity scattering rely on the evaluation of increasingly complicated scattering amplitudes which come with an extremely high CPU cost.
High Energy Physics - Phenomenology
PulseSatellite: A tool using human-AI feedback loops for satellite image analysis in humanitarian contexts
Humanitarian response to natural disasters and conflicts can be assisted by satellite image analysis.
Automated Speech Generation from UN General Assembly Statements: Mapping Risks in AI Generated Texts
This work is aligned with the efforts of the United Nations and other civil society organisations to highlight potential political and societal risks arising through the malicious use of text generation software, and their potential impact on human rights.
XNet: A convolutional neural network (CNN) implementation for medical X-Ray image segmentation suitable for small datasets
X-Ray image enhancement, along with many other medical image processing applications, requires the segmentation of images into bone, soft tissue, and open beam regions.
