Exploring the performance-power-energy balance of low-power multicore and manycore architectures for anomaly detection in remote sensing.
Germán LeónJosé M. MoleroEster M. GarzónInmaculada GarcíaAntonio J. PlazaEnrique S. Quintana-OrtíPublished in: J. Supercomput. (2015)
Keyphrases
- anomaly detection
- remote sensing
- low power
- power consumption
- energy efficiency
- energy dissipation
- ultra low power
- intrusion detection
- change detection
- low cost
- multispectral
- high speed
- detecting anomalies
- image analysis
- remote sensing images
- high resolution
- image processing
- power reduction
- network traffic
- data assimilation
- power dissipation
- intrusion detection system
- land cover
- graphics processing units
- unsupervised learning
- energy consumption
- data center
- one class support vector machines
- detect anomalies
- machine learning
- neural network
- digital camera
- real time
- climate change
- cmos technology
- hidden markov models
- pattern recognition