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Segmentation Convolutional Neural Networks for Automatic Crater Detection on Mars
- Source :
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 12(8):2944-2957
- Publication Year :
- 2019
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2019.
-
Abstract
- Accepted: 2019-05-04<br />資料番号: SA1190128000
- Subjects :
- Atmospheric Science
geology
010504 meteorology & atmospheric sciences
Computer science
0211 other engineering and technologies
02 engineering and technology
01 natural sciences
Convolutional neural network
remote sensing
Impact crater
planets
Segmentation
Computers in Earth Sciences
image segmentation
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Pixel
Artificial neural network
business.industry
Model selection
Pattern recognition
Crater counting
Feature extraction
Artificial intelligence
F1 score
business
Subjects
Details
- Language :
- English
- ISSN :
- 19391404
- Volume :
- 12
- Issue :
- 8
- Database :
- OpenAIRE
- Journal :
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Accession number :
- edsair.doi.dedup.....86279b01739e249c6c9cb2c307508376