A review of computer graphics approaches to urban modeling from a machine learning perspective

作     者：Tian FENG Feiyi FAN Tomasz BEDNARZ Tian FENG;Feiyi FAN;Tomasz BEDNARZ

作者机构：Department of Computer Science and Information TechnologyLa Trobe UniversityVIC 3086Australia Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190China Expanded Perception and Interaction CentreUniversity of New South WalesNSW 2021Australia CSIRO's Data61NSW 2015Australia 

出 版 物：《Frontiers of Information Technology & Electronic Engineering》 (信息与电子工程前沿（英文版）)

年 卷 期：2021年第22卷第7期

页      面：915-925页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 0839[工学-网络空间安全] 081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Urban modeling Computer graphics Machine learning Deep learning 

摘      要：Urban modeling facilitates the generation of virtual environments for various scenarios about *** requires expertise and consideration,and therefore consumes massive time and computation ***,related tasks sometimes result in dissatisfaction or even *** challenges have received significant attention from researchers in the area of computer ***,the burgeoning development of artificial intelligence motivates people to exploit machine learning,and hence improves the conventional *** this paper,we present a review of approaches to urban modeling in computer graphics using machine learning in the literature published between 2010 and *** serves as an overview of the current state of research on urban modeling from a machine learning perspective.