Title:
Detecting Mosquitoes with Convolutional Neural Networks
Detecting Mosquitoes with Convolutional Neural Networks
Author(s)
Moore, Lawrence S.
Advisor(s)
Hays, James
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Abstract
Mosquitoes are directly responsible for the death of more than a million people each year. Yet the ability to mitigate their deadly impact or even monitor them in the wild to better understand their behavior remains relatively limited. One of the primary reasons for this lack of progress is the difficulty in locating and tracking an individual mosquito, leading to only estimates for a population as a whole. To address this problem, this research discusses several approaches using computer vision to detect and track the flight of mosquitoes. In particular, we discuss the performance of several convolutional neural network architectures which show promising results. Once these techniques are refined to give a high enough degree of accuracy, this vision system could be used in conjunction with drones to track and eliminate mosquitoes in both an indoor and outdoor setting.
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Date Issued
2017-08
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Resource Type
Text
Resource Subtype
Undergraduate Thesis