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by   -   May 29, 2020

Galaxy

Researchers have developed a model for generating pixel-level morphological classifications of astronomical sources. Morpheus can analyze astronomical image data pixel-by-pixel to identify and classify all of the galaxies and stars in large data sets from astronomy surveys.

by   -   May 27, 2020

Volcano Mount Etna

By Sarah Wild

Dr Luciano Zuccarello grew up in the shadow of Mount Etna, an active volcano on the Italian island of Sicily. Farms and orchards ring the lower slopes of the volcano, where the fertile soil is ideal for agriculture. But the volcano looms large in the life of locals because it is also one of the most active volcanoes in the world.

More than 29 million people globally live within 10km of a volcano, and understanding volcanoes’ behaviour – and being able to predict when they are going to erupt or spew ash into the air – is vital for safeguarding people’s wellbeing.

by   -   May 25, 2020
CT scans
Qualitative results for five different cases from the test set. The top row shows the image slice, the second row shows the ground-truth segmentation, and the bottom row shows the predicted segmentation given by the CNN model.

Researchers have developed an algorithm that can detect and identify different types of brain injuries. The team, from the University of Cambridge, Imperial College London and CONICET, have clinically validated and tested their method on large sets of CT scans and found that it was successfully able to detect, segment, quantify and differentiate different types of brain lesions.

by   -   May 18, 2020
Cecilia Mascolo
Professor Cecilia Mascolo at the University of Cambridge, UK, hopes her coronavirus sounds app could provide the data needed to build a quick and cheap Covid-19 screening test in the future. Image credit – Salvatore Scellato

By Richard Gray

A recording of a cough, the noise of a person’s breathing or even the sound of their voice could be used to help diagnose patients with Covid-19 in the future, according to Professor Cecilia Mascolo, co-director of the centre for mobile, wearable systems and augmented intelligence at the University of Cambridge, UK.

Prof. Mascolo has developed a sound-collecting app to help train machine learning algorithms to detect the tell-tale sounds of coronavirus infection. Created as part of a project called EAR, she hopes it might eventually lead to new ways of diagnosing respiratory diseases and help in the global fight against coronavirus.

by   -   May 4, 2020

AI patent denied
Last summer it was reported that patents had been filed in the USA and Europe listing an artificial intelligence system as the inventor. The patents in question were for a food container and a warning light and were filed by Stephen Thaler on behalf of DABUS (an AI system). Those applications have been considered, and on 22 April the US patent and trademark office (USPTO) reached the same verdict as the UK and European offices, denying the patents.

by   -   April 30, 2020

Li-ion batteries
Researchers have developed a machine learning method that can predict battery health with ten times higher accuracy than current industry standard, which could aid in the development of safer and more reliable batteries for electric vehicles and consumer electronics.

by   -   April 29, 2020


Researchers in Korea have developed a convolutional neural network (CNN) architecture capable of aiding specialists in the diagnosis of 134 skin disorders. Their algorithm can also predict treatment options. With the assistance of this method, the team found that the diagnostic accuracy of dermatologists as well as the general public was significantly improved.

by   -   April 24, 2020

AI song contest

The 2020 Eurovision Song Contest may have been cancelled, but fans of formulaic pop can still get their fill courtesy of the VPRO AI Song Contest. The contestants and their entries were revealed on 10 April and the public have until 10 May to cast their votes.

by   -   April 22, 2020

AIhub ambassador

Are you a PhD student or researcher with an interest in science communication? We are recruiting AIhub Ambassadors to help us write about the latest news, research, conferences, and more, in the field of artificial intelligence and machine learning.

wearable devices sleep

Getting diagnosed with a sleep disorder or assessing quality of sleep is an often expensive and tricky proposition, involving sleep clinics where patients are hooked up to sensors and wires for monitoring.

Wearable devices, such as the Fitbit and Apple Watch, offer less intrusive and more cost-effective sleeping monitoring, but the tradeoff can be inaccurate or imprecise sleep data.

Researchers at the Georgia Institute of Technology are working to combine the accuracy of sleep clinics with the convenience of wearable computing by developing machine learning models, or smart algorithms, that provide better sleep measurement data as well as considerably faster, more energy-efficient software.




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