EMDS-5: Environmental Microorganism image dataset Fifth Version for multiple image analysis tasks.

Environmental Microorganism Data Set Fifth Version (EMDS-5) is a microscopic image dataset including original Environmental Microorganism (EM) images and two sets of Ground Truth (GT) images. The GT image sets include a single-object GT image set and a multi-object GT image set. EMDS-5 has 21 types...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Zihan Li, Chen Li, Yudong Yao, Jinghua Zhang, Md Mamunur Rahaman, Hao Xu, Frank Kulwa, Bolin Lu, Xuemin Zhu, Tao Jiang
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/cac9a5ecaa234c42ab8833e6afed667d
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:cac9a5ecaa234c42ab8833e6afed667d
record_format	dspace
spelling	oai:doaj.org-article:cac9a5ecaa234c42ab8833e6afed667d2021-12-02T20:05:40ZEMDS-5: Environmental Microorganism image dataset Fifth Version for multiple image analysis tasks.1932-620310.1371/journal.pone.0250631https://doaj.org/article/cac9a5ecaa234c42ab8833e6afed667d2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0250631https://doaj.org/toc/1932-6203Environmental Microorganism Data Set Fifth Version (EMDS-5) is a microscopic image dataset including original Environmental Microorganism (EM) images and two sets of Ground Truth (GT) images. The GT image sets include a single-object GT image set and a multi-object GT image set. EMDS-5 has 21 types of EMs, each of which contains 20 original EM images, 20 single-object GT images and 20 multi-object GT images. EMDS-5 can realize to evaluate image preprocessing, image segmentation, feature extraction, image classification and image retrieval functions. In order to prove the effectiveness of EMDS-5, for each function, we select the most representative algorithms and price indicators for testing and evaluation. The image preprocessing functions contain two parts: image denoising and image edge detection. Image denoising uses nine kinds of filters to denoise 13 kinds of noises, respectively. In the aspect of edge detection, six edge detection operators are used to detect the edges of the images, and two evaluation indicators, peak-signal to noise ratio and mean structural similarity, are used for evaluation. Image segmentation includes single-object image segmentation and multi-object image segmentation. Six methods are used for single-object image segmentation, while k-means and U-net are used for multi-object segmentation. We extract nine features from the images in EMDS-5 and use the Support Vector Machine (SVM) classifier for testing. In terms of image classification, we select the VGG16 feature to test SVM, k-Nearest Neighbors, Random Forests. We test two types of retrieval approaches: texture feature retrieval and deep learning feature retrieval. We select the last layer of features of VGG16 network and ResNet50 network as feature vectors. We use mean average precision as the evaluation index for retrieval. EMDS-5 is available at the URL:https://github.com/NEUZihan/EMDS-5.git.Zihan LiChen LiYudong YaoJinghua ZhangMd Mamunur RahamanHao XuFrank KulwaBolin LuXuemin ZhuTao JiangPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 5, p e0250631 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Zihan Li Chen Li Yudong Yao Jinghua Zhang Md Mamunur Rahaman Hao Xu Frank Kulwa Bolin Lu Xuemin Zhu Tao Jiang EMDS-5: Environmental Microorganism image dataset Fifth Version for multiple image analysis tasks.
description	Environmental Microorganism Data Set Fifth Version (EMDS-5) is a microscopic image dataset including original Environmental Microorganism (EM) images and two sets of Ground Truth (GT) images. The GT image sets include a single-object GT image set and a multi-object GT image set. EMDS-5 has 21 types of EMs, each of which contains 20 original EM images, 20 single-object GT images and 20 multi-object GT images. EMDS-5 can realize to evaluate image preprocessing, image segmentation, feature extraction, image classification and image retrieval functions. In order to prove the effectiveness of EMDS-5, for each function, we select the most representative algorithms and price indicators for testing and evaluation. The image preprocessing functions contain two parts: image denoising and image edge detection. Image denoising uses nine kinds of filters to denoise 13 kinds of noises, respectively. In the aspect of edge detection, six edge detection operators are used to detect the edges of the images, and two evaluation indicators, peak-signal to noise ratio and mean structural similarity, are used for evaluation. Image segmentation includes single-object image segmentation and multi-object image segmentation. Six methods are used for single-object image segmentation, while k-means and U-net are used for multi-object segmentation. We extract nine features from the images in EMDS-5 and use the Support Vector Machine (SVM) classifier for testing. In terms of image classification, we select the VGG16 feature to test SVM, k-Nearest Neighbors, Random Forests. We test two types of retrieval approaches: texture feature retrieval and deep learning feature retrieval. We select the last layer of features of VGG16 network and ResNet50 network as feature vectors. We use mean average precision as the evaluation index for retrieval. EMDS-5 is available at the URL:https://github.com/NEUZihan/EMDS-5.git.
format	article
author	Zihan Li Chen Li Yudong Yao Jinghua Zhang Md Mamunur Rahaman Hao Xu Frank Kulwa Bolin Lu Xuemin Zhu Tao Jiang
author_facet	Zihan Li Chen Li Yudong Yao Jinghua Zhang Md Mamunur Rahaman Hao Xu Frank Kulwa Bolin Lu Xuemin Zhu Tao Jiang
author_sort	Zihan Li
title	EMDS-5: Environmental Microorganism image dataset Fifth Version for multiple image analysis tasks.
title_short	EMDS-5: Environmental Microorganism image dataset Fifth Version for multiple image analysis tasks.
title_full	EMDS-5: Environmental Microorganism image dataset Fifth Version for multiple image analysis tasks.
title_fullStr	EMDS-5: Environmental Microorganism image dataset Fifth Version for multiple image analysis tasks.
title_full_unstemmed	EMDS-5: Environmental Microorganism image dataset Fifth Version for multiple image analysis tasks.
title_sort	emds-5: environmental microorganism image dataset fifth version for multiple image analysis tasks.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/cac9a5ecaa234c42ab8833e6afed667d
work_keys_str_mv	AT zihanli emds5environmentalmicroorganismimagedatasetfifthversionformultipleimageanalysistasks AT chenli emds5environmentalmicroorganismimagedatasetfifthversionformultipleimageanalysistasks AT yudongyao emds5environmentalmicroorganismimagedatasetfifthversionformultipleimageanalysistasks AT jinghuazhang emds5environmentalmicroorganismimagedatasetfifthversionformultipleimageanalysistasks AT mdmamunurrahaman emds5environmentalmicroorganismimagedatasetfifthversionformultipleimageanalysistasks AT haoxu emds5environmentalmicroorganismimagedatasetfifthversionformultipleimageanalysistasks AT frankkulwa emds5environmentalmicroorganismimagedatasetfifthversionformultipleimageanalysistasks AT bolinlu emds5environmentalmicroorganismimagedatasetfifthversionformultipleimageanalysistasks AT xueminzhu emds5environmentalmicroorganismimagedatasetfifthversionformultipleimageanalysistasks AT taojiang emds5environmentalmicroorganismimagedatasetfifthversionformultipleimageanalysistasks
_version_	1718375449682247680

EMDS-5: Environmental Microorganism image dataset Fifth Version for multiple image analysis tasks.

Ejemplares similares