Spatiotemporal data fusion is a cost-effective way to produce remote sensing images with high spatial and temporal resolutions using multisource images. Using spectral unmixing analysis interpolation, the flexible spatiotemporal (FSDAF) algorithm suitable for heterogeneous landscapes capable of capturing abrupt land-cover changes. However, extensive computational complexity FSDAF prevents its u...

Emerging heterogeneous multiprocessor chips will integrate a large number of different computational units: e.g., large cores for sequential processing, several smaller cores for parallel processing, Graphics Processing Units (GPUs), media accelerators, helper processors, Digital Signal Processors (DSPs), embedded FPGAs, and application-specific hardware circuits. These units are designed speci...

A combined local and global optimisation approach to crystal structure determination from powder diffraction data (SDPD) is presented. Using graphics processing units (GPUs) accelerate the underpinning calculations, speed...

In this paper we address the massive parallelization of the characterization of heartbeats by means of Graphics Processors. Heartbeats are represented with Hermite polynomials due to the compactness and robustness of this representation. Both the off-line and on-line characterization of QRS complexes are covered, thus, assessing the capabilities of Graphics Processors for these tasks. The resul...

My research goal is to develop application-driven geometric algorithms for computer aided design and manufacturing that are provably correct in theory and robust in practice. Much of my current work has the theme of visibility, accessibility, and/or interference analysis, with applications in parallel CAD evaluation, design for manufacturing for casting and injection molding, virtual design env...