Insect interaction analysis based on object detection and CNN
Insect interaction analysis based on object detection and CNN
复制标题
基于目标检测和CNN的昆虫交互分析
DOI：
--
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
D. Carval
中科院分区：
文献类型：
--
作者：
Paul Tresson;P. Tixier;W. Puech;D. Carval
直接观察研究生物多样性可能是耗时的，然而，其他方法往往提供间接测量，并可能有偏见。为了解决这些问题，图像可以成为一个有用的工具，生态学家已经开始越来越多地依赖图像作为数据来源和自动图像分析。然而，现有的方法大多是对图像进行分类。本文提出了一种基于目标检测的图像深层信息获取方法。使用高分辨率图像，我们建立了一个管道来切割原始图像，执行检测，然后改进这些观察结果。我们通过在农林业香蕉-咖啡系统中拍摄的现场图像来研究香蕉害虫Cosmopolites sodidus和Metamasius sp.周围的无脊椎动物群落以及该群落中不同动物之间的相互作用，从而说明了该管道的兴趣。实验结果表明，我们的流水线达到87.8%的f1得分，可以成功地检测和识别23个物种和蚂蚁种姓。这23个物种被分为7个超级类，但蚂蚁超级类的个体和相互作用更多，被描述得更精确。然后，我们能够研究该群落不同物种之间的相互作用网络，并确定该生态系统中香蕉害虫的主要捕食者。
Direct observation to study biodiversity can be time consuming, however, other methods often provide indirect measurements and are possibly biased. To solve these problems, images can be a useful tool and ecologists have started to rely more and more on images as a source of data and on automated image analysis. However, the existing methods mostly perform image classification. In this paper we present an efficient method based on object detection to access deeper information the content of an image. Using high resolution images, we built a pipeline to slice the original images, perform detections and later refine these observations. We illustrate the interest of this pipeline by using it on-field images taken in agroforestery banana-coffee systems to study invertebrate communities around the banana pests Cosmopolites sodidus and Metamasius sp. and the interactions between the different animals within this community. Experimental results show that our pipeline reaches 87.8% F1-score and allows us to successfully detect and identify 23 species and ant castes. These 23 species are divided into 7 super-classes, but the ant super-class, that shows more individuals and interactions is described more precisely. We are then able to study the interaction network between different species of this community and identify major predators of banana pests within this ecosystem.