606,619 research outputs found

    The Public Eye

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    Fast and Accurate Algorithm for Eye Localization for Gaze Tracking in Low Resolution Images

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    Iris centre localization in low-resolution visible images is a challenging problem in computer vision community due to noise, shadows, occlusions, pose variations, eye blinks, etc. This paper proposes an efficient method for determining iris centre in low-resolution images in the visible spectrum. Even low-cost consumer-grade webcams can be used for gaze tracking without any additional hardware. A two-stage algorithm is proposed for iris centre localization. The proposed method uses geometrical characteristics of the eye. In the first stage, a fast convolution based approach is used for obtaining the coarse location of iris centre (IC). The IC location is further refined in the second stage using boundary tracing and ellipse fitting. The algorithm has been evaluated in public databases like BioID, Gi4E and is found to outperform the state of the art methods.Comment: 12 pages, 10 figures, IET Computer Vision, 201

    The Population Biology and Transmission Dynamics of Loa loa

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    Endemic to Central Africa, loiasis – or African eye worm (caused by the filarial nematode Loa loa) – affects more than 10 million people. Despite causing ocular and systemic symptoms, it has typically been considered a benign condition, only of public health relevance because it impedes mass drug administration-based interventions against onchocerciasis and lymphatic filariasis in co-endemic areas. Recent research has challenged this conception, demonstrating excess mortality associated with high levels of infection, implying that loiasis warrants attention as an intrinsic public health problem. This review summarises available information on the key parasitological, entomological, and epidemiological characteristics of the infection and argues for the mobilisation of resources to control the disease, and the development of a mathematical transmission model to guide deployment of interventions

    Exploring celebrity influence on public attitude towards the COVID-19 pandemic: social media shared sentiment analysis

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    The COVID-19 pandemic has introduced new opportunities for health communication, including an increase in the public use of online outlets for health-related emotions. People have turned to social media networks to share sentiments related to the impacts of the COVID-19 pandemic. In this paper we examine the role of social messaging shared by Persons in the Public Eye (i.e. athletes, politicians, news personnel) in determining overall public discourse direction. We harvested approximately 13 million tweets ranging from 1 January 2020 to 1 March 2022. The sentiment was calculated for each tweet using a fine-tuned DistilRoBERTa model, which was used to compare COVID-19 vaccine-related Twitter posts (tweets) that co-occurred with mentions of People in the Public Eye. Our findings suggest the presence of consistent patterns of emotional content co-occurring with messaging shared by Persons in the Public Eye for the first two years of the COVID-19 pandemic influenced public opinion and largely stimulated online public discourse. We demonstrate that as the pandemic progressed, public sentiment shared on social networks was shaped by risk perceptions, political ideologies and health-protective behaviours shared by Persons in the Public Eye, often in a negative light.Comment: 7 Pages, 4 Figure
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