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  • New Publication in Machine Vision and Applications
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New Publication in IEEE International Conference on Electronics, Circuits and Systems

Published October 17, 2017 at 10:16 am - No Comments

Hyper-parameters of a machine learning architecture define its design. Tuning of hyper-parameters is costly and for large data sets outright impractical, whether it is performed manually or algorithmically. In this study we propose a Neocognitron based method for reducing the training set to a fraction, while keeping the dynamics and complexity of the domain. Our […]

New publication in Machine Vision and Applications

Published May 17, 2015 at 9:51 am - No Comments

In particle filtering, dimensionality of the state space can be reduced by tracking control (or feature) points as independent objects, which are traditionally named as partitions. Two critical decisions have to be made in implementation of reduced state-space dimensionality. First is how to construct a dynamic (transition) model for partitions that are inherently dependent. Second […]

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