Nov 19, 2007 · Abstract: In this letter, we have developed a neural network (NN) based upon modeling fields for improved object tracking.
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Abstract—In this letter, we have developed a neural network (NN) based upon modeling fields for improved object tracking. Models for ground moving target ...
In this letter, we have developed a neural network (NN) based upon modeling fields for improved object tracking. Models for ground moving target indicator ...
Perlovsky, L., & Deming, R. (2007). Neural networks for improved ...
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This paper considers the fundamental argument against free will, so called reductionism, and why the choice for dualism against monism, follows logically. Then, ...
Oct 8, 2024 · This paper advances a recently introduced hybrid model-based and data-driven method called neural-enhanced belief propagation (NEBP).
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Posted: Jul 9, 2017
Posted: Jul 9, 2017
Recurrent neural networks improve tracking capabilities by leveraging their ability to maintain a memory of previous observations, enabling them to model the ...
This paper presents a DNN-based algorithm as an add- on module that improves the tracking performance of a classical feedback controller. Given a desired ...
Oct 20, 2016 · This paper presents a DNN-based algorithm as an add-on module that improves the tracking performance of a classical feedback controller. Given a ...
This paper presents a method for improving the estimation accuracy of a tracking Kalman filter (TKF) by using a multilayered neural network (MNN).