A Deep Learning‐based Computer Vision Approach for Comparative Monarch Butterfly Phenotype Identification in Citizen Science

In recent years, the monarch butterfly's iconic migration patterns have come under threat from a number of factors, climate change to pesticide use. To track trends in their populations, scientists as well citizen must identify individuals accurately. This is key because there exist other species butterfly, such viceroy butterflies, that are “look-alikes,” having similar phenotypes. tackle this problem and aid more efficient identification, we present MonarchNet, first comprehensive dataset consisting butterfly imagery for monarchs five look-alike species. We train baseline deep-learning classification model serve tool differentiating butterflies its various look-alikes. seek contribute study biodiversity ecology by providing novel method computational these particular The ultimate aim help population most precise manner possible.