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Extraction of the essential features from massive bands is a key issue in hyperspectral images classification. Plenty of feature extraction techniques can be found in the literature but most of these methods rely on the linear/stationary assumptions. The aim of this paper is to propose an alternative methodology based on the ensemble empirical mode decomposition (EEMD) and utilize the versatile support...
In this paper, we study travel time and energy cost prediction at any future departure time for a targeted road segment and vehicle. These two prediction tasks play an important part in the design of advanced driver-assistance systems (ADAS) that can automatically manage battery charging, energy saving, and route planning for fully electric vehicles. Compared with the fundamental problem of travel...
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