Single model irregular-region retrieval for rapid plant disease detection

用于快速植物病害检测的单模型不规则区域检索

• 批准号: DP180100958
• 负责人: Prof Yongsheng Gao
• 金额: $ 28.21万
• 依托单位: Griffith University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2018
• 资助国家: 澳大利亚
• 起止时间: 2018-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP180100958
• 关键词: Single; model; irregular; region; retrieval

This project aims to study the major technical barrier in plant disease image retrieval to build a pervasive rapid plant disease identification system. The techniques are designed to function on one or very few sample images, thus enabling on-line in field disease identification linked to authoritative plant disease image libraries. The success of this project will not only make significant contributions to fundamental theory in single model image retrieval, but also create a revolution in plant disease early detection for effective and efficient crop protection.

本项目旨在研究植物病害图像检索的主要技术障碍，建立一个普适的植物病害快速识别系统。该技术被设计为在一个或很少的样品图像上起作用，从而使得能够在田间进行与权威的植物病害图像库相关联的在线病害识别。该项目的成功不仅将为单模型图像检索的基础理论研究做出重大贡献，而且将为植物病害的早期检测和有效的作物保护带来一场革命。