Arid
DOI10.1145/3303714.3303732
Increase the Exploitation of Mars Satellite Images Via Deep Learning Techniques
AlMarzooqi, Mariam; AlNaqbi, Asayel; AlMheiri, Aysha; Bezawada, Srikanth; Mohamed, Elfadil A.; Zaki, Nazar
通讯作者Zaki, Nazar
会议名称International Conference on Robotics, Control and Automation Engineering (RCAE) / International Conference on Advanced Mechanical and Electrical Engineering (AMEE)
会议日期DEC 26-28, 2018
会议地点Beijing, PEOPLES R CHINA
英文摘要

Mars is the fourth planet from the sun and the second smallest planet in the solar system after Mercury. Like Earth, Mars has a range of surface features such as valleys, deserts, and polar ice caps. Scientists around the globe have developed a specific interest in the terrain and climate of Mars because it is believed to have the potential to host life. To assist scientists to discover past or present life on Mars, we developed machine learning models (based on deep learning) to analyze the satellite images received from the Red Planet. The models automatically eliminated satellite images that were of a low quality and subsequently classified the high-quality images based on climate/environmental conditions. The models were tested on sample datasets and demonstrated the ability to achieve considerable accuracy. We also integrated additional functionality to convert two-dimensional (2D) satellite images into an informative (3D) format for better analysis and exploration. Furthermore, the solution was integrated into a mobile application that can be used by scientists and members of the public who are interested in space science.


英文关键词Mars space science deep learning NIMA satellite images 3D images
来源出版物PROCEEDINGS OF INTERNATIONAL CONFERENCE ON ROBOTICS, CONTROL AND AUTOMATION ENGINEERING (RAE 2018) AND INTERNATIONAL CONFERENCE ON ADVANCED MECHANICAL AND ELECTRICAL ENGINEERING (AMEE 2018)
出版年2018
页码171-175
EISBN978-1-4503-6102-6
出版者ASSOC COMPUTING MACHINERY
类型Proceedings Paper
语种英语
国家U Arab Emirates
收录类别CPCI-S
WOS记录号WOS:000473331800034
WOS关键词QUALITY ASSESSMENT
WOS类目Automation & Control Systems ; Computer Science, Theory & Methods ; Robotics
WOS研究方向Automation & Control Systems ; Computer Science ; Robotics
资源类型会议论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/307874
作者单位United Arab Emirates Univ, Coll Informat Technol, Al Ain 15551, U Arab Emirates
推荐引用方式
GB/T 7714
AlMarzooqi, Mariam,AlNaqbi, Asayel,AlMheiri, Aysha,et al. Increase the Exploitation of Mars Satellite Images Via Deep Learning Techniques[C]:ASSOC COMPUTING MACHINERY,2018:171-175.
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