陕西师范大学学报（自然科学版）2024，Vol.52Issue(2)：89-101,13.DOI:10.15983/j.cnki.jsnu.2024003
图卷积神经网络综述
The review of the graph convolutional neural networks
摘要
Abstract
Graph convolutional neural network(GCN)has emerged as the intersection of graph theory and deep learning,becoming the hotspot research field of machine learning.Therefore,a comprehensive overview of the GCN is provided,and the available studies of GCN into two typical categories are summarized:spectral-based methods and spatial-based methods.These two typical types of GCN models are extensively discussed,the fundamental theoretical underpinnings of the graph convolution operations are delved into,diverse applications of GCN across various domains are showcased,the major challenges encountered by GCN are summarized,and valuable insights into the future trends of GCN advancement are offerred.Additionally,the potential utilization of GCN in butterfly recognition tasks is investigated,particularly in identifying butterfly species by leveraging images captured in natural habitats.关键词
图卷积神经网络/谱方法/空间方法/目标检测Key words
graph convolutional neural network/spectral methods/spatial methods/object detection分类
信息技术与安全科学引用本文复制引用
谢娟英,张建宇..图卷积神经网络综述[J].陕西师范大学学报（自然科学版）,2024,52(2):89-101,13.基金项目
国家自然科学基金(62076159,61673251,12031010) （62076159,61673251,12031010）
中央高校基本科研业务费项目(GK202105003) （GK202105003）
