基于机器学习的外来入侵植物叶片图像识别方法

Leaf Image Recognition Method of Alien Invasive Plants Based on Machine Learning

为了有效避免外来入侵植物打破当地植物自身的生长环境,提出一种基于机器学习的外来入侵植物叶片图像识别方法.通过基于指数变量的自适应扩张图像滤波算法对外来入侵植物叶片图像滤波处理.构建金字塔卷积网络,提取轮廓纹理特征并且融合,采用softmax函数获取最终的外来入侵植物叶片图像识别结果.通过实验测试证明,所提方法可以有效降低外来入侵植物叶片图像识别时间,提升识别结果准确性,同时所提方法可以在各种应用场景中提供高效、准确的图像处理和识别能力.

In order to effectively prevent invasive plants from breaking the growth environment of local plants,a method of leaf image recognition of invasive plants based on machine learning is proposed.An adaptive expanded image filtering algorithm based on exponential variables is used to filter the image of the alien invasive plant leaves.The pyramid convolution network is constructed,the contour texture features are extracted and fused,and the softmax function is used to obtain the final recognition results of the alien invasive plant leaf image.Experimental tests show that the proposed method can effectively reduce the recognition time of alien invasive plant leaf images and improve the accuracy of recognition results.At the same time,the proposed method can provide efficient and accurate image processing and recognition capabilities in various application scenarios.