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A novel vision system with unique algorithms to recognise, count & size apples on trees to greatly improve crop forecasting and management to maximise yield and optimise market price - Applecount -

A novel vision system with unique algorithms to recognise, count & size apples on trees to greatly improve crop forecasting and management to maximise yield and optimise market price - Applecount -
一种新颖的视觉系统,具有独特的识别、计数算法
批准号:
710522
负责人:
金额:
$12.14万
依托单位国家:
英国
项目类别:
GRD Proof of Concept
财政年份:
2014
资助国家:
英国
项目状态:
已结题
起止时间:
2014 至 --

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中文摘要
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英文摘要
The UK is not self sufficient in apples, even during the high season, providing only one thirdof our own consumption, with the shortfall made up by imports. A large proportion of this isdue to our inability to meet demand for class1 fruit – the stringent specification set bysupermarkets, representing 80% of sales. Our client records show that similar orchards canhave outputs that vary by over 60% on the same cultivars, both on the overall tonnage yieldper hectare, and on the percentage of substandard fruit, with reject fruit going to waste or lowvalue processing and losing up to 80% of its value. A significant proportion of this variation isdown to management practice and crop forecasting.The market price is dependent on crop quality and the crop yield declared by the growers andwholesalers, and these estimates tend to be inaccurate with a variation of typically +/- 20%from final yield. This has a major impact on market price. Quotas are agreed with thesupermarkets early in the season, and must be fulfilled. Over-estimating yield meanspurchasing imports (at late in season high prices) to cover the shortfall, while underestimatingyield, means losing profits by selling excess crop to low value outlets or even forpigfeed. A key part of management practice is to know when and how to ‘thin’ crops topromote selective growth, and this is very dependent on knowing accurately how many applesthere are on each tree at various times in the growing season.Our client who represents one third of UK growers, believes that by standardising bestpracticeorchard management, and with a strategic approach to helping breed new cultivars,we could enable UK orchards to take back at least 100,000T of lost import volume, worth£50M.This project aims to create & prove the effectiveness of a novel vision based cropmeasurement technology for apple growers, capable of measuring apples while on the trees.
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基于SOPC的VisionTransformer模型AI推理系统实现研究
老年人群视障风险VISION管控模式构建与实证研究
  • 批准号:
    71974198
  • 项目类别:
    面上项目
  • 资助金额:
    48.5万元
  • 批准年份:
    2019
  • 负责人:
    王爱平
  • 依托单位: