The applications of machine learning in insect identification and classification on sticky card in agricultural setting

Sunday, November 10, 2024

11:42 AM – 11:54 AM MST

Location: Phoenix Convention Center, 223

Presenting Author(s)

Jamal Hunter

PhD Student
University of Georgia
Athens, Georgia

Co-Author(s)

PS

Paul Severns

University of Georgia
Athens, Georgia
AA

Angelita L. Acebes-Doria (she/her/hers)

Research Biologist
USDA-ARS
Hilo, Hawaii
GR

Glen Rains

University of Georgia
Tifton, Georgia
Brett R. Blaauw

Associate Professor
University of Georgia
Athens, Georgia

Agriculture is highly impacted by arthropod communities and one of the most effective ways to monitor those communities is through passive and active traps like sticky cards. Whilst sticky cards are easy to use, they do, however, require a large amount of time and expertise to process once they have been collected. Our goal is to use machine learning to reduce the amount of time and expertise needed to fully realize the potential sticky card deployment has. This presentation will discuss the development progression and current status of our sticky card processing algorithm as a tool to provide users with a quick summary of insect communities from images of sticky cards.