MonarchNet：区分帝王蝶和具有相似表型的蝶类
MonarchNet: Differentiating Monarch Butterflies from Butterflies Species with Similar Phenotypes
摘要：
近年来，帝王蝶标志性的迁徙模式受到了从气候变化到杀虫剂使用等一系列因素的威胁。为了跟踪其人口的趋势，科学家和公民科学家必须准确地识别个体。这对于帝王蝶的研究来说是独一无二的关键，因为还有其他种类的蝴蝶，如总督蝶，它们是“长相相似”（由濒危野生动植物种国际贸易公约创造），具有相似的表型。为了解决这个问题，并帮助更有效地识别，我们提出了MonarchNet，这是第一个由帝王蝶和五种相似物种的蝴蝶图像组成的综合数据集。我们训练一个基线深度学习分类模型，作为区分帝王蝶及其各种类似物的工具。我们寻求有助于生物多样性和蝴蝶生态学的研究，提供了一种新的方法，这些特定的蝴蝶物种的计算分类。最终目的是帮助科学家以最精确和最有效的方式跟踪帝王蝶的种群和迁徙趋势。
英文摘要：
In recent years, the monarch butterfly's iconic migration patterns have come under threat from a number of factors, from climate change to pesticide use. To track trends in their populations, scientists as well as citizen scientists must identify individuals accurately. This is uniquely key for the study of monarch butterflies because there exist other species of butterfly, such as viceroy butterflies, that are "look-alikes" (coined by the Convention on International Trade in Endangered Species of Wild Fauna and Flora), having similar phenotypes. To tackle this problem and to aid in more efficient identification, we present MonarchNet, the first comprehensive dataset consisting of butterfly imagery for monarchs and five look-alike species. We train a baseline deep-learning classification model to serve as a tool for differentiating monarch butterflies and its various look-alikes. We seek to contribute to the study of biodiversity and butterfly ecology by providing a novel method for computational classification of these particular butterfly species. The ultimate aim is to help scientists track monarch butterfly population and migration trends in the most precise and efficient manner possible.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
