Conceptual low-cost on-board high performance computing in CubeSat nanosatellites for pattern recognition in Earth's remote sensing.
Jorge Javier Hernández-GómezG. A. Yañez-CasasAlejandro M. Torres-LaraCarlos Couder-CastañedaMauricio Gabriel Orozco-del-CastilloJuan Carlos Valdiviezo-NavarroI. MedinaA. Solís-SantoméD. Vázquez-ÁlvarezP. I. Chávez-LópezPublished in: iGISc (2019)
Keyphrases
- remote sensing
- high performance computing
- low cost
- pattern recognition
- image analysis
- image processing
- scientific computing
- multispectral
- massively parallel
- change detection
- computational science
- remote sensing images
- computing systems
- remote sensing imagery
- high resolution
- hyperspectral
- parallel computing
- remote sensing data
- grid computing
- earth science
- fault tolerance
- computing environments
- satellite images
- machine learning
- computing resources
- computer vision
- energy efficiency
- land cover
- environmental sciences
- neural network
- satellite data
- remote sensed images
- embedded systems
- cost effective
- geographical information systems
- earth observation
- automatic image registration
- load balancing
- sensor networks
- high quality
- feature extraction