干旱区生态环境知识资源中心(Arid): ACHENY: A standard Chenopodiaceae image dataset for deep learning models

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DOI	10.1016/j.dib.2021.107478
	ACHENY: A standard Chenopodiaceae image dataset for deep learning models
	Heidary-Sharifabad, Ahmad; Zarchi, Mohsen Sardari; Emadi, Sima; Zarei, Gholamreza
通讯作者	Heidary-Sharifabad, A (corresponding author)，Islamic Azad Univ, Dept Comp Engn, Maybod Branch, Maybod, Iran.
来源期刊	DATA IN BRIEF
ISSN	2352-3409
出版年	2021
卷号	39
英文摘要	This paper contains datasets related to the Efficient Deep Learning Models for Categorizing Chenopodiaceae in the wild (Heidary-Sharifabad et al., 2021). There are about 1500 species of Chenopodiaceae that are spread worldwide and often are ecologically important. Biodiversity conservation of these species is critical due to the destructive effects of human activities on them. For this purpose, identification and surveillance of Chenopodiaceae species in their natural habitat are necessary and can be facilitated by deep learning. The feasibility of applying deep learning algorithms to identify Chenopodiaceae species depends on access to the appropriate relevant dataset. Therefore, ACHENY dataset was collected from natural habitats of different bushes of Chenopodiaceae species, in realworld conditions from desert and semi-desert areas of the Yazd province of IRAN. This imbalanced dataset is compiled of 27,030 RGB color images from 30 Chenopodiaceae species, each species 300-1461 images. Imaging is performed from multiple bushes for each species, with different camera-totarget distances, viewpoints, angles, and natural sunlight in November and December. The collected images are not preprocessed, only are resized to 224 x224 dimensions which can be used on some of the successful deep learning models and then were grouped into their respective class. The images in each class are separated by 10% for testing, 18% for validation, and 72% for training. Test images are often manually selected from plant bushes different from the training set. Then training and validation images are randomly separated from the remaining images in each category. The smallsized images with 64 x 64 dimensions also are included in ACHENY which can be used on some other deep models. (C) 2021 The Authors. Published by Elsevier Inc.
英文关键词	Biodiversity protection Chenopodiaceae Deep learning Image classification Plant classification
类型	Article
语种	英语
开放获取类型	Green Published, gold
收录类别	ESCI
WOS记录号	WOS:000743794900025
WOS类目	Multidisciplinary Sciences
WOS研究方向	Science & Technology - Other Topics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/376065
作者单位	[Heidary-Sharifabad, Ahmad] Islamic Azad Univ, Dept Comp Engn, Maybod Branch, Maybod, Iran; [Zarchi, Mohsen Sardari] Meybod Univ, Dept Comp Engn, Meybod, Iran; [Emadi, Sima] Islamic Azad Univ, Dept Comp Engn, Yazd Branch, Yazd, Iran; [Zarei, Gholamreza] Islamic Azad Univ, Dept Agron, Maybod Branch, Maybod, Iran
推荐引用方式 GB/T 7714	Heidary-Sharifabad, Ahmad,Zarchi, Mohsen Sardari,Emadi, Sima,et al. ACHENY: A standard Chenopodiaceae image dataset for deep learning models[J],2021,39.
APA	Heidary-Sharifabad, Ahmad,Zarchi, Mohsen Sardari,Emadi, Sima,&Zarei, Gholamreza.(2021).ACHENY: A standard Chenopodiaceae image dataset for deep learning models.DATA IN BRIEF,39.
MLA	Heidary-Sharifabad, Ahmad,et al."ACHENY: A standard Chenopodiaceae image dataset for deep learning models".DATA IN BRIEF 39(2021).