Skip navigation


  • DSpace logo
  • Home
  • Collections
  • Researcher Profile
  • Explore by
    • Researcher Profile
  • VGU library
  • Help
  • User Guide
  • Sign on to:
    • My DSpace
    • Receive email
      updates
    • Edit Account details

VGU RESEARCH REPOSITORY


Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/1879
DC FieldValueLanguage
dc.contributor.authorNgo Phuc Linhen_US
dc.date.accessioned2024-11-18T06:53:24Z-
dc.date.available2024-11-18T06:53:24Z-
dc.date.issued2023-
dc.identifier.urihttps://epub.vgu.edu.vn/handle/dlibvgu/1879-
dc.description.abstractLarvae source management (LSM) is a control strategy for detecting and controlling mosquito populations by targeting the immature stages of mosquitoes, i.e., larvae. The identification of water bodies would play a crucial role and signification method in controlling mosquito populations. Implementing Unmanned aerial vehicles (UAV) for identifying breeding sites would be considered as a practical solution to address the problem. In my thesis, I would like to present a model for detecting temporary water bodies taken by drone-captured images collected in the Vietnamese-German University area and Binh Duong province. For my experiments, I use an RGB dataset image which includes temporary water bodies labeled a bounding box by the LabelImg application and then training and detecting by YOLOv7 algorithm. My result shows that the YOLOv7 algorithm trained models could discriminate the appearance of water bodies where mosquitoes could be bred with overall average accuracy mean Average Precision (mAP) over five times training is 69.2%. The model also labels water bodies’ imagery to create a dataset for training computer vision models and could be applied for further researchen_US
dc.language.isoenen_US
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectTemporary water bodiesen_US
dc.subjectUnmanned aerial vehiclesen_US
dc.subjectYOLOv7 algorithmen_US
dc.subjectObject detectionen_US
dc.titleAutomatic detection of water bodies with potential mosquito larvae ground from image captured by an UAV droveen_US
dc.typeThesisen_US
item.fulltextWith Fulltext-
item.languageiso639-1other-
item.grantfulltextrestricted-
Appears in Collections:Computer Science (CS)
Files in This Item:
File Description SizeFormat Existing users please Login
Automatic detection of water bodies with potential mosquito larvae ground from image captured by an UAV drove.pdf12.58 MBAdobe PDF
Show simple item record

Page view(s)

127
checked on Nov 15, 2025

Download(s)

41
checked on Nov 15, 2025

Google ScholarTM

Check


This item is licensed under a Creative Commons License Creative Commons

© Copyright 2020 by Vietnamese - German University Library.
Add: Ring road 4, Quarter 4, Thoi Hoa Ward, Ben Cat City, Binh Duong Province
Tel.:(0274) 222 0990. Ext.: 70206