Thanikkal Jibi G, Dubey Ashwani Kumar, Thomas M T
Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University Uttar Pradesh, Noida, U.P. 201313 India.
Department of Electronics and Communication Engineering, Amity School of Engineering and Technology, Amity University Uttar Pradesh, Noida, U.P. 201313 India.
Wirel Pers Commun. 2023 Apr 21:1-17. doi: 10.1007/s11277-023-10476-3.
In the Covid-19 pandemic situation, the world is looking for immunity-boosting techniques for fighting against coronavirus. Every plant is medicine in one or another way, but Ayurveda explains the uses of plant-based medicines and immunity boosters for specific requirements of the human body. To help Ayurveda, botanists are trying to identify more species of medicinal immunity-boosting plants by evaluating the characteristics of the leaf. For a normal person, detecting immunity-boosting plants is a difficult task. Deep learning networks provide highly accurate results in image processing. In the medicinal plant analysis, many leaves are like each other. So, the direct analysis of leaf images using the deep learning network causes many issues for medicinal plant identification. Hence, keeping the requirement of a method at large to help all human beings, the proposed leaf shape descriptor with the deep learning-based mobile application is developed for the identification of immunity-boosting medicinal plants using a smartphone. SDAMPI algorithm explained numerical descriptor generation for closed shapes. This mobile application achieved 96%accuracy for the 64 × 64 sized images.
在新冠疫情形势下，全世界都在寻找增强免疫力以对抗冠状病毒的技术。每种植物都以某种方式具有药用价值，但阿育吠陀医学解释了基于植物的药物和免疫增强剂针对人体特定需求的用途。为了助力阿育吠陀医学，植物学家们正试图通过评估叶子的特征来识别更多具有增强免疫力功效的药用植物物种。对于普通人来说，检测具有增强免疫力功效的植物是一项艰巨的任务。深度学习网络在图像处理中能提供高度准确的结果。在药用植物分析中，许多叶子彼此相似。因此，直接使用深度学习网络对叶子图像进行分析会给药用植物识别带来诸多问题。所以，考虑到帮助所有人的方法的需求，我们开发了基于深度学习的带有移动应用程序的叶形描述符，用于通过智能手机识别具有增强免疫力功效的药用植物。SDAMPI算法解释了封闭形状的数值描述符生成方法。该移动应用程序对64×64尺寸的图像实现了96%的准确率。
