J. M. Molero

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—Anomaly detection is an important task for hyperspec-tral data exploitation. Although many algorithms have been developed for this purpose in recent years, due to the large dimensionality of hyperspectral image data, fast anomaly detection remains a challenging task. In this work, we exploit the computational power of commodity graphics processing units(More)
Remotely sensed hyperspectral sensors provide image data containing rich information in both the spatial and the spectral domain, and this information can be used to address detection tasks in many applications. One of the most widely used and successful algorithms for anomaly detection in hyperspectral images is the RX algorithm. Despite its wide(More)
Anomaly detection is an important task for hyperspectral data exploitation. A standard approach for anomaly detection in the literature is the method developed by Reed and Yu, also called RX algorithm. It implements the Mahalanobis distance, which has been widely used in hyperspectral imaging applications. A variation of this algorithm, known as kernel RX(More)
In this paper, we perform an experimental study of the interactions between execution time (i.e., performance), power, and energy that occur in modern low-power architectures when executing the RX algorithm for detecting anomalies in hyperspectral images (i.e., signatures which are spectrally different from their surrounding data). We believe this is(More)
cipantes es propuesta en 3 conglomerados: (1) Risky Innovators; (2) Inventors; y (3) Consistent Innovators. Abstract Innovation is a process that faces several " market failure " situations and for this reason – and for being considered one of the main drivers of economic growth throughout the world – a large number of governmental and supranational(More)
As we have addressed in an earlier article, quantitative evaluation of R&D policies often approaches the outcomes of initiatives without effectively considering differential impacts on economic agents. Our goal is to confirm the existence of " segments " of firms according to their outcomes arising from participation in a given R&D program. firms.(More)
Remotely sensed hyperspectral sensors provide image data containing rich information in both the spatial and the spectral domain, and this information can be used to address detection tasks in many applications. In many surveillance applications, the size of the objects (targets) searched for constitutes a very small fraction of the total search area and(More)
This paper focus on how local partners learn and develop competences within networks whose central actor is a foreign-owned firm. It combines an analysis of learning processes in networks with an assessment of the effects of key foreign investment projects. Following a case study method, two large automotive projects undertaken by Renault and by Ford and(More)
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