Victor Rodrigues

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Random Forests (RF) and Boosting are two of the most successful supervised learning paradigms for automatic classification. In this work we propose to combine both strategies in order to exploit their strengths while simultaneously solving some of their drawbacks, especially when applied to high-dimensional and noisy classification tasks. More specifically,(More)
Catadioptric Vision Systems have wide vision field of 360-degree of the environment explored, using combination of lenses and mirrors. It is commonly used in structured indoor environments with static obstacles and when submitted in applications operating in outdoor(and rural) environments, encourage arbitrary and various issues that affect the processing(More)
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