论文标题
基于集成的Yolo算法的蝴蝶检测和分类
Butterfly Detection and Classification Based on Integrated YOLO Algorithm
论文作者
论文摘要
昆虫是地球上丰富的物种，昆虫的识别和鉴定的任务是复杂而艰巨的。在当前研究中，如何将人工智能技术和数字图像处理方法应用于自动识别昆虫物种是一个热门问题。在本文中，研究了自动检测和分类识别蝴蝶照片的问题，并提出了一种适合蝴蝶分类的生物标记方法。根据YOLO算法，提出了基于Yolo算法的蝴蝶自动检测和分类识别算法，通过合成Yolo模型的结果，提出了蝴蝶自动检测和分类识别算法。它极大地提高了Yolo算法的概括能力，并使其具有更好的解决样本问题的能力。实验结果表明，提出的注释方法和综合的Yolo算法在蝴蝶自动检测和识别方面具有很高的精度和识别率。
Insects are abundant species on the earth, and the task of identification and identification of insects is complex and arduous. How to apply artificial intelligence technology and digital image processing methods to automatic identification of insect species is a hot issue in current research. In this paper, the problem of automatic detection and classification recognition of butterfly photographs is studied, and a method of bio-labeling suitable for butterfly classification is proposed. On the basis of YOLO algorithm, by synthesizing the results of YOLO models with different training mechanisms, a butterfly automatic detection and classification recognition algorithm based on YOLO algorithm is proposed. It greatly improves the generalization ability of YOLO algorithm and makes it have better ability to solve small sample problems. The experimental results show that the proposed annotation method and integrated YOLO algorithm have high accuracy and recognition rate in butterfly automatic detection and recognition.
