NEC06665 Automatic image recognition for Japanese Knotweed for the conveyancing sector

我们将通过一系列活动来弥补我们目前的知识差距，这些活动旨在提高我们对市场需求和潜在最终用户的理解，并制作一个概念验证图像分类器。概念验证算法-使用超过8，000张日本虎杖的图像和超过20，000张其他常见园林植物的图像，我们将产生一个概念验证图像分类算法，可以识别日本虎杖的图像，并估计确定性，并可与日本虎杖风险地图相结合，以全面评估该物种出现在地产上的可能性。建立这种概念验证是后续资金的关键，因为它将成为未来任何应用的基础。此外，该技术的局限性和能力是未知的，直到一个分类器已经建立和评估。RICS咨询-我们将与测量师行业组织皇家特许测量师协会（RICS）进行咨询，讨论行业需求差距、市场规模，并制定图像分类器的评估标准。了解市场和特定的最终用户将是后续应用的关键。通过之前与RICS的合作，我们知道他们是日本虎杖调查和修复行业的专家，他们可以为识别图像分类工具的市场做出重大贡献，并将我们与可能参与后续应用的最终用户联系起来。分类器报告-该项目将整理日本虎杖的图像，主要来自生物记录中心的系统'iRecord'。我们将报告图像的可用性，图像和模型选择对分类器精度的影响，计算要求，以及分类器在“真实世界”条件下能够达到的精度。该项目在可用图像和分类器准确性方面的技术限制是识别特定最终用户应用程序的关键。这一理解将用于确定后续应用的目标，并为共同设计阶段选择最终用户。代码库-我们将生成一个代码库，用于设计，训练和实现图像分类器，这将是后续应用程序的基础。这个代码库将是CEH的知识产权，来自CEH的数据和图像，这将构成后续应用程序的核心。

We will address our current knowledge gaps with a programme of activities aimed at increasing our understanding of the market need and potential end-users, as well as producing a proof-of-concept image classifier.Work to be undertaken:Proof-of-concept algorithm - Using over 8,000 images of Japanese Knotweed and over 20,000 images of other common garden plants, we will produce a proof-of-concept image classification algorithm that can identify images of Japanese Knotweed, with an estimate of certainty, and can be integrated with the Japanese Knotweed risk map to provide an overall assessment of the likelihood of the species being present on a property. Building this proof-of-concept is key for follow-on funding as it will be the basis of any future application. Additionally, the limitations and capabilities of the technique are unknown until a classifier has been built and evaluated. A functional proof-of-concept should increase stakeholder recruitment and engagement in the follow-on application.RICS consultation - We will consult with the Royal Institute of Chartered Surveyors (RICS) as the trade body for surveyors to discuss the needs gap in the industry, the size of the market and to set out the evaluation criteria of the image classifier. Understanding the market and the specific end-users will be key to the follow-on application. Through previous work with RICS, we know that they are experts in Japanese Knotweed surveying and remediation industry and they can contribute significantly to identifying markets for an image classification tool, as well as connecting us with end-users who could be involved in a follow-on application.Classifier report - The project will collate images of Japanese Knotweed, primarily from the Biological Records Centre's system 'iRecord'. We will report on the availability of images, the impact of image and model selection on classifier accuracy, the computational requirements, and the accuracy that the classifiers are able to achieve in 'real-world' conditions. The technical limitations of the project, both in terms of images available, and the accuracy of the classifier are key for identifying specific end user applications. This understanding will be used to specify objectives for the follow-on application and to select end-users for the co-design phase. Code base - We will produce a library of code for designing, training, and implementing image classifiers which will be the basis of the follow-on application. This code base will be the intellectual property of CEH, derived from CEH's data and image holdings, which will form the core of the follow-on application.