Search Results for author: Joseph Bullock

Found 6 papers, 3 papers with code

Considerations, Good Practices, Risks and Pitfalls in Developing AI Solutions Against COVID-19

no code implementations13 Aug 2020 Alexandra Luccioni, Joseph Bullock, Katherine Hoffmann Pham, Cynthia Sin Nga Lam, Miguel Luengo-Oroz

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

no code implementations25 Mar 2020 Joseph Bullock, Alexandra Luccioni, Katherine Hoffmann Pham, Cynthia Sin Nga Lam, Miguel Luengo-Oroz

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

1 code implementation18 Feb 2020 Simon Badger, Joseph Bullock

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

Automated Speech Generation from UN General Assembly Statements: Mapping Risks in AI Generated Texts

1 code implementation5 Jun 2019 Joseph Bullock, Miguel Luengo-Oroz

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.

Text Generation

XNet: A convolutional neural network (CNN) implementation for medical X-Ray image segmentation suitable for small datasets

2 code implementations3 Dec 2018 Joseph Bullock, Carolina Cuesta-Lazaro, Arnau Quera-Bofarull

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.

Image Enhancement Medical X-Ray Image Segmentation +1

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