Hyperspectral imaging is an indispensable technology for many remote sensing
applications, yet expensive in terms of computing resources. It requires significant …

Hyperspectral images contain tens to hundreds of bands, implying a high spectral
resolution. This high spectral resolution allows for obtaining a precise signature of structures …

With the development of computer architecture, even for embedded systems, GPU devices
can be integrated, providing outstanding performance and energy efficiency to meet the …

Huge amounts of data have been generated on edge devices every day, which requires
efficient data analytics and management. However, due to the limited computing capacity of …

Real-time hyperspectral imaging on-board compression represents a critical processing
step in many remote sensing applications where the acquired hyperspectral data need to be …

Hyperspectral data processing is a computationally intensive task that is usually performed
in high-performance computing clusters. However, in remote sensing scenarios, where …

As GPU applications expand, the reliability of GPU is drawing more attention since even
reliability-demanding applications are executed on GPUs. Silent data corruption (SDC) is …

Traditional reliability approaches introduce relevant costs to achieve unconditional
correctness during data processing. However, many application environments are inherently …

Image processing applications exhibit an intrinsic degree of fault tolerance due to i) the
redundant nature of images, and ii) the possible ability of the consumers of the application …

New generation airborne embedded system has deployed Graphical Processing Units
(GPUs) to raise processing capability to meet growing computational demands. Comparing …