From beasts to bytes: Revolutionizing zoological research with artificial intelligence
Yujuan Zhang, 重庆师范大学生命科学学院重庆市媒介昆虫重点实验室, 重庆市动物生物学重点实验室, 重庆401331, 中国, Zeyu Luo, Yawen Sun, Junhao Liu, Zongqing Chen, 重庆师范大学数学科学学院, 重庆 401331, 中国, 重庆师范大学重庆国家应用数学研究中心, 重庆 401331, 中国
Abstract
Since the late 2010s, Artificial Intelligence (AI) including machine learning, boosted through deep learning, has boomed as a vital tool to leverage computer vision, natural language processing and speech recognition in revolutionizing zoological research. This review provides an overview of the primary tasks, core models, datasets, and applications of AI in zoological research, including animal classification, resource conservation, behavior, development, genetics and evolution, breeding and health, disease models, and paleontology. Additionally, we explore the challenges and future directions of integrating AI into this field. Based on numerous case studies, this review outlines various avenues for incorporating AI into zoological research and underscores its potential to enhance our understanding of the intricate relationships that exist within the animal kingdom. As we build a bridge between beast and byte realms, this review serves as a resource for envisioning novel AI applications in zoological research that have not yet been explored.