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Memory-efficient particle filter recurrent neural network for object localization
This study proposes a novel memory-efficient recurrent neural network (RNN) architecture specified to solve the object localization problem.
Multiparticle Kalman filter for object localization in symmetric environments
Two well-known classes of filtering algorithms to solve the localization problem are Kalman filter-based methods and particle filter-based methods.
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