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It is well-known that ensemble of classifiers can achieve higher accuracy compared to a single classifier system. This paper pays attention to ensemble systems consisting of multiple feature extractors and multiple classifiers (MFMC). However, MFMC increases the system complexity dramatically, leading to a highly complex combinatorial optimization problem. In order to overcome the complexity while...
For pedestrian detection in ADAS, using multiple classifiers generally performs better than using a single classifier in terms of accuracy since the classifiers can be made to complement one another. On the other hand, such a pedestrian detector needs to be tuned dynamically to the variation of real-world environment such as different poses of pedestrians and variable background. Thus the system is...
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