Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Aiden Nibali"'
Autor:
Abraham Albert Bonela, Aiden Nibali, Zhen He, Benjamin Riordan, Dan Anderson-Luxford, Emmanuel Kuntsche
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-9 (2023)
Abstract Exposure to alcohol content in media increases alcohol consumption and related harm. With exponential growth of media content, it is important to use algorithms to automatically detect and quantify alcohol exposure. Foundation models such as
Externí odkaz:
https://doaj.org/article/1fd92654a08d4c69aab543f19cb28940
Autor:
Brandon Victor, Aiden Nibali, Saul Justin Newman, Tristan Coram, Francisco Pinto, Matthew Reynolds, Robert T. Furbank, Zhen He
Publikováno v:
Remote Sensing, Vol 16, Iss 2, p 282 (2024)
To ensure global food security, crop breeders conduct extensive trials across various locations to discover new crop varieties that grow more robustly, have higher yields, and are resilient to local stress factors. These trials consist of thousands o
Externí odkaz:
https://doaj.org/article/a6b464d38ff045cb8698d88f4849cf65
Autor:
Abraham Albert Bonela, Zhen He, Aiden Nibali, Thomas Norman, Peter G. Miller, Emmanuel Kuntsche
Publikováno v:
Alcohol. 109:49-54
Acute alcohol intoxication impairs cognitive and psychomotor abilities leading to various public health hazards such as road traffic accidents and alcohol-related violence. Intoxicated individuals are usually identified by measuring their blood alcoh
Purpose: Increasing access to marker-less technology has enabled practitioners to obtain kinematic data more quickly. However, the validation of many of these methods is lacking. Therefore, the validity of pre-trained neural networks was explored in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d0e0bc9400919f3c7bdcca4c79b0825
https://doi.org/10.21203/rs.3.rs-2774614/v1
https://doi.org/10.21203/rs.3.rs-2774614/v1
Advances in deep neural networks have led to significant improvement of object detection accuracy. However, object detection in crowded scenarios is a challenging task for neural networks since extremely overlapped objects provide fewer visible cues
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7cf0c1c566f20796919074ff8a9706c1
Publikováno v:
Machine Vision and Applications. 33
We introduce a novel deep learning based group activity recognition approach called the Pose Only Group Activity Recognition System (POGARS), designed to use only tracked poses of people to predict the performed group activity. In contrast to existin
Autor:
Brandon Victor, Stuart Morgan, Aiden Nibali, Marc Elipot, Ashley Hall, Matthias Langer, Zhen He
Publikováno v:
Neural Computing and Applications. 33:7205-7223
It is very important for swimming coaches to analyse a swimmer’s performance at the end of each race, since the analysis can then be used to change strategies for the next round. Coaches rely heavily on statistics, such as stroke length and instant
Publikováno v:
Computer methods and programs in biomedicine. 216
Medical image classification is often challenging for two reasons: a lack of labelled examples due to expensive and time-consuming annotation protocols, and imbalanced class labels due to the relative scarcity of disease-positive individuals in the w
Publikováno v:
IEEE Internet of Things Journal. 6:7116-7121
Commensal rats and mice are a major pest. Commercial-scale control measures require frequent manual checking of rodenticide levels in bait stations and searching for evidence of activity. In this paper, we propose a low power remote monitoring system
Sophisticated trajectory prediction models that effectively mimic team dynamics have many potential uses for sports coaches, broadcasters and spectators. However, through experiments on soccer data we found that it can be surprisingly challenging to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::70d91e59671317c7b1a1887d3aec6093