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In the past few years, segmentation and classification techniques have become a cornerstone of many successful remote sensing algorithms aiming at delineating geographic target objects. One common strategy relies on using multiple complex features to guide the delineation process with the objective of gathering complementary information for improving classification results. However, a persistent problem...
The ever-growing access to high-resolution images has prompted the development of region-based classification methods for remote sensing images. However, in agricultural applications, the recognition of specific regions is still a challenge as there could be many different spectral patterns in a same studied area. In this context, depending on the features used, different learning methods can be used...
Recognizing different kinds of fruits and vegetables is a common task in supermarkets. This task, however, poses several challenges as it requires the identification of different species of a particular produce and also its variety. Usually, existing computer-based recognition approaches are not automatic and demand long-term and laborious prior training sessions. This paper presents a novel framework...
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