In search of relevant things: A novel approach for image analysis.

寻找相关事物：图像分析的新颖方法。

• 批准号: FT190100623
• 负责人: Prof Antonio Di Ieva
• 金额: $ 71.43万
• 依托单位: Macquarie University
• 依托单位国家: 澳大利亚
• 项目类别: ARC Future Fellowships
• 财政年份: 2020
• 资助国家: 澳大利亚
• 起止时间: 2020-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/FT190100623
• 关键词: search; relevant; things; novel; approach

This project aims to investigate how experts’ cognitive processes may be transferred to computers for the automatic recognition of visual features. By merging computer and brain sciences, the project will characterise the way the brains of experts understand what is seen, in order to translate such a process in a new computer vision tool. This should provide significant benefits, such as automatic detection of threats or diseases in satellite and diagnostic imaging, respectively, among other applications. For the first time, the combination of how a computer analyses an image and how an expert interprets it will be used as a common language to enable machines to process visual information in a manner that mimics the way human brains do.

本研究旨在探讨如何将专家的认知过程转移到计算机上，以自动识别视觉特征。通过融合计算机和脑科学，该项目将研究专家的大脑理解所看到的东西的方式，以便将这种过程转化为新的计算机视觉工具。这将带来巨大的好处，例如在卫星和诊断成像中分别自动检测威胁或疾病，以及其他应用。这是第一次，计算机如何分析图像以及专家如何解释图像的结合将被用作一种通用语言，使机器能够以模仿人脑的方式处理视觉信息。