Dataset of vector mosquito images

Mosquitoes pose substantial threat to public health resulting in million number of deaths wordlwide every year. They act as the vectors responsible for diseases such as Dengue, Yellow fever,Chikungunya, Zika etc. The harmful mosquito species are contained in the genera Aedes, Anopheles and Culex. Au...

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Main Authors: Reshma Pise, Kailas Patil, Meena Laad, Neeraj Pise
Format: Article
Language:English
Published: Elsevier 2022-12-01
Series:Data in Brief
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352340922007806
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author Reshma Pise
Kailas Patil
Meena Laad
Neeraj Pise
author_facet Reshma Pise
Kailas Patil
Meena Laad
Neeraj Pise
author_sort Reshma Pise
collection DOAJ
description Mosquitoes pose substantial threat to public health resulting in million number of deaths wordlwide every year. They act as the vectors responsible for diseases such as Dengue, Yellow fever,Chikungunya, Zika etc. The harmful mosquito species are contained in the genera Aedes, Anopheles and Culex. Automated species identification of vectors is essential to implement targeted vector control strategies. The objective of the proposed paper is to construct a novel dataset of images of dangerous mosquito species. We have prepared a dataset of images of adult mosquitoes belonging to three species: Aedes Aegypti, Anopheles stephensi and Culex quinquefasciatus stored in two folders. The first folder comprises of total 2640 augmented images of mosquitoes belonging to the three species. The second folder contains original images of the the three species. The dataset is valuable for training machine and deep learning models for automatic species classification.
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spelling doaj.art-b1046309c5874ef7a81e7979ef5945432022-12-22T04:17:40ZengElsevierData in Brief2352-34092022-12-0145108573Dataset of vector mosquito imagesReshma Pise0Kailas Patil1Meena Laad2Neeraj Pise3Research scholar, Vishwakarma University, Pune, India; Corresponding authors.Professor, Vishwakarma University, Pune, India; Corresponding authors.Professor, Symbiosis Institute of Technology, Pune, IndiaGraduate student, Computer Science , Rutgers University, New Brunswick NJ, United StatesMosquitoes pose substantial threat to public health resulting in million number of deaths wordlwide every year. They act as the vectors responsible for diseases such as Dengue, Yellow fever,Chikungunya, Zika etc. The harmful mosquito species are contained in the genera Aedes, Anopheles and Culex. Automated species identification of vectors is essential to implement targeted vector control strategies. The objective of the proposed paper is to construct a novel dataset of images of dangerous mosquito species. We have prepared a dataset of images of adult mosquitoes belonging to three species: Aedes Aegypti, Anopheles stephensi and Culex quinquefasciatus stored in two folders. The first folder comprises of total 2640 augmented images of mosquitoes belonging to the three species. The second folder contains original images of the the three species. The dataset is valuable for training machine and deep learning models for automatic species classification.http://www.sciencedirect.com/science/article/pii/S2352340922007806Computer visionDeep learningMosquito classificationVector control
spellingShingle Reshma Pise
Kailas Patil
Meena Laad
Neeraj Pise
Dataset of vector mosquito images
Data in Brief
Computer vision
Deep learning
Mosquito classification
Vector control
title Dataset of vector mosquito images
title_full Dataset of vector mosquito images
title_fullStr Dataset of vector mosquito images
title_full_unstemmed Dataset of vector mosquito images
title_short Dataset of vector mosquito images
title_sort dataset of vector mosquito images
topic Computer vision
Deep learning
Mosquito classification
Vector control
url http://www.sciencedirect.com/science/article/pii/S2352340922007806
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