Semantic Segmentation of High Resolution Satellite Imagery using Generative Adversarial Networks with Progressive Growing

Autor:	Subodh Kalia, Sanmay Ganguly, Supratik Mukhopadhyay, Andrew Michaelis, Shuang Li, Edward Collier, G. Shreekant, Geri Madanguit, Ramakrishna R. Nemani, Auroop R. Ganguly, Kate Duffy
Rok vydání:	2021
Předmět:	010504 meteorology & atmospheric sciences Computer science business.industry 0211 other engineering and technologies High resolution 02 engineering and technology Machine learning computer.software_genre 01 natural sciences Adversarial system ComputerApplications_MISCELLANEOUS Urbanization Earth and Planetary Sciences (miscellaneous) Satellite imagery Segmentation Artificial intelligence InformationSystems_MISCELLANEOUS Electrical and Electronic Engineering business computer Generative grammar 021101 geological & geomatics engineering 0105 earth and related environmental sciences
Zdroj:	Remote Sensing Letters. 12:439-448
ISSN:	2150-7058 2150-704X
Popis:	With increase in urbanization and Earth Sciences research into urban areas, the need to quickly and accurately segment urban rooftop maps has never been greater. Current machine learning techniques...
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::f82232aad2fa3f888faa895d0014ff5e https://doi.org/10.1080/2150704x.2021.1895444 Zobrazit plný text záznamu