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I-Corps: Optical design and the development of high accuracy automated tick classification using computer vision

I-Corps: Optical design and the development of high accuracy automated tick classification using computer vision
I-Corps:使用计算机视觉进行光学设计和高精度自动蜱分类的开发
批准号:
10561399
负责人:
Autumn Goodwin
金额:
$5.5万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-04-18 至 2022-06-30

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中文摘要
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英文摘要
Abstract The incidence of US tick-borne diseases has more than doubled in the last two decades. Due to lack of effective vaccines for tick-borne diseases, prevention of tick bites remains the primary focus of disease mitigation. Tick vector surveillance - monitoring an area to understand tick species composition, abundance, and spatial distribution - is key to providing the public with accurate and up-to-date information when they are in areas of high risk, and enabling precision vector control when necessary. Vectech is an NIH SBIR phase I awardee seeking to develop the first automated imaging and identification system capable of instantaneously and accurately identifying the top nine tick vectors in the US. The approach of standardized optical design and development of a computer vision system offers several advantages over conventional acarologist identification. This NIH I-Corps project seeks to improve understanding of tick surveillance needs in the US. The proposed I-Corps team will focus on the commercial opportunity to improve clinical decision making for administration of tick bite prophylaxis and enhancing public health information for vector control organizations and the general public. The resulting insights will be incorporated into Vectech’s future research with the aim of bringing a commercial product to market.
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High accuracy automated tick classification using computer vision
  • 批准号:
    10699845
  • 项目类别:
  • 资助金额:
    $95.04万
  • 财政年份:
    2022
  • 负责人:
    Autumn Goodwin
  • 依托单位:
Optical design and the development of high accuracy automated tick classification using computer vision
  • 批准号:
    10325667
  • 项目类别:
  • 资助金额:
    $29.57万
  • 财政年份:
    2021
  • 负责人:
    Autumn Goodwin
  • 依托单位:
海外基金