Dataset

MUSIC for P3 dataset

Version :v1/v2

Last Modified :Fri, 26 Jan 2018 JST

solar power plant detection

The number of photovoltaic power plants is growing so rapidly that we must rely on satellite observations and efficient machine learning methods for the global monitoring. MUSIC for P3 (Photovoltaic Power Plants) is a training and validation dataset generated by AIRC/AIST to support such a global survey of photovoltaic power plants.

Detailed Information :https://github.com/gistairc/MUSIC4P3

Creator :	Geoinformation Service Research Team, Digital Architecture Research Center, National Institute of Advanced Industrial Science and Technology Contact : m-gsrt-contact[at]aist.go.jp
License :	Custom License https://github.com/gistairc/MUSIC4P3/blob/master/LICENSE.md
First Publication Date :	Tue, 17 Oct 2017 JST
Citation :	Tomohiro Ishii, Edgar Simo-Serra, Satoshi Iizuka, Yoshihiko Mochizuki, Akihiro Sugimoto, Ryosuke Nakamura, Hiroshi Ishikawa ,“Detection by Classification of Buildings in Multispectral Satellite Imagery,” ICPR 2016. (pdf) Nevrez Imamoglu, Motoki Kimura, Hiroki Miyamoto, Aito Fujita, Ryosuke Nakamura,“Solar Power Plant Detection on Multi-Spectral Satellite Imagery using Weakly-Supervised CNN with Feedback Features and m-PCNN Fusion,” BMVC 2017. (pdf)

Updated on Tue, 25 Oct 2022 11:24:40 JST