首页 | 本学科首页   官方微博 | 高级检索  
   检索      

国内8款常用植物识别软件的识别能力评价
引用本文:许展慧,刘诗尧,赵莹,涂文琴,常诏峰,张恩涛,郭靖,郑迪,耿鋆,顾高营,郭淳鹏,郭璐璐,王静,徐春阳,彭钏,杨腾,崔梦琪,孙伟成,张剑坛,刘皓天,巴超群,王鹤琪,贾竞超,武金洲,肖翠,马克平.国内8款常用植物识别软件的识别能力评价[J].生物多样性,2020,28(4):524-766.
作者姓名:许展慧  刘诗尧  赵莹  涂文琴  常诏峰  张恩涛  郭靖  郑迪  耿鋆  顾高营  郭淳鹏  郭璐璐  王静  徐春阳  彭钏  杨腾  崔梦琪  孙伟成  张剑坛  刘皓天  巴超群  王鹤琪  贾竞超  武金洲  肖翠  马克平
作者单位:1 中国科学院大学, 北京 100049
2 中国科学院植物研究所植被与环境变化国家重点实验室, 北京 100093
基金项目:中国科学院战略性先导科技专项(XDA19050404)
摘    要:随着智能手机和人工智能技术的发展, 以手机app为载体的植物识别软件慢慢走进公众生活、科普活动和科研活动的各个方面。植物识别app的识别正确率是决定其使用价值和用户体验的关键因素。目前, 国内应用市场上有许多植物识别app, 它们的开发目的和应用范围各异, 软件本身的关注点、数据库来源、算法、硬件要求也存在很大差异。对于不同人群, 植物识别app有不同的意义, 如对于科研人员来说, 识别能力强的app是提高效率的一大工具; 对植物爱好者来说, 具一定准确率的识别app可以作为入门的工具。因此, 对各app的识别能力进行分析与评价显得尤为重要。本文选取了8款常用的app, 分别对400张已准确鉴定的植物图片进行识别, 其中干旱半干旱区、温带、热带和亚热带4个区各选取100张。这些图片共计122科164属340种, 涵盖了乔木、灌木、草本、草质藤本和木质藤本5种生长型, 包含23种国家级保护植物。种、属、科准确识别正确分别计4分、2分、1分, 以此标准对软件识别能力按总得分进行排序, 正确率得分由高到低依次为花帮主、百度识图、花伴侣、形色、花卉识别、植物识别、发现识花、微软识花。

关 键 词:植物识别软件  花帮主  百度识图  花伴侣  形色  花卉识别  植物识别  发现识花  微软识花  
收稿时间:2019-09-01

Evaluation of the identification ability of eight commonly used plant identification application softwares in China
Zhanhui Xu,Shiyao Liu,Ying Zhao,Wenqin Tu,Zhaofeng Chang,Entao Zhang,Jing Guo,Di Zheng,Jun Geng,Gaoying Gu,Chunpeng Guo,Lulu Guo,Jing Wang,Chunyang Xu,Chuan Peng,Teng Yang,Mengqi Cui,Weicheng Sun,Jiantan Zhang,Haotian Liu,Chaoqun Ba,Heqi Wang,Jingchao Jia,Jinzhou Wu,Cui Xiao,Keping Ma.Evaluation of the identification ability of eight commonly used plant identification application softwares in China[J].Biodiversity Science,2020,28(4):524-766.
Authors:Zhanhui Xu  Shiyao Liu  Ying Zhao  Wenqin Tu  Zhaofeng Chang  Entao Zhang  Jing Guo  Di Zheng  Jun Geng  Gaoying Gu  Chunpeng Guo  Lulu Guo  Jing Wang  Chunyang Xu  Chuan Peng  Teng Yang  Mengqi Cui  Weicheng Sun  Jiantan Zhang  Haotian Liu  Chaoqun Ba  Heqi Wang  Jingchao Jia  Jinzhou Wu  Cui Xiao  Keping Ma
Institution:1 University of Chinese Academy of Sciences, Beijing 100049
2 State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093
Abstract:Smart phone and artificial intelligence technology development has led to various plant recognition softwares on mobile applications. These applications have gradually entered all aspects of public life, popular science activities, and scientific research activities. Presently, there are many plant recognition apps in China, which have varying development purposes and application scopes. Among these differences include variation in software concerns, database sources, algorithms, and hardware which could implicate large discrepancies between apps, making it important to analyze and evaluate the accuracy, scope of application and potential use of each software. In this paper, eight apps were selected to identify 400 accurately identified plant photos, 100 photos being chosen from arid and semi-arid zones, temperate zones, tropical zones, and subtropical zones, respectively. In total, these photos belong to 122 families, 164 genera and 340 species, covering five growth forms of trees, shrubs, herbs, herbaceous vines and woody vines, as well as 23 national protected plant species. Accurate identification of species, genera and families was scored 4, 2 and 1 points, respectively. The software recognition ability was sorted according to total scores, and the results are as follows: HuaBangZhu, Baidu-Shitu, HuaBanLv, XingSe, Huahui-Shibie, Zhiwu-Shibie, Faxian-Shihua, Flower Recognition.
Keywords:Plant recognition software  HuaBangZhu  Baidu-Shitu  HuaBanLv  XingSe  Huahui-Shibie  Zhiwu-Shibie  Faxian-Shihua  Flower recognition  
点击此处可从《生物多样性》浏览原始摘要信息
点击此处可从《生物多样性》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号