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SA2 is open-source software, which means complete transparency and scalability in terms of algorithm implementation.
We provide implementation details of the learning process and the complete algorithm.
ImageJ software59 was used; we used EDF algorithm implementation for ImageJ software as previously described60.
We provide detailed algorithm implementation description.
The complete algorithm is detailed below (Algorithm 4).
EM conducted method and algorithm implementation, with data analysis.
Genetic Algorithm Optimization Toolbox (GAOT) [ 21] was used for Genetic Algorithm implementation.
In contrast, the purpose of our contribution is to present an efficient partitioning of a monocular FastSLAM2.0 on a heterogeneous embedded architecture and to provide the first complete GPGPU implementation of the algorithm with a focus on general purpose processing unite.
In practice, we can use the explicit expression of ℒ in Problem 2 for stopping the iterations, e.g. when the relative improvement on ℒ falls below a specified threshold τ>0: To complete the implementation of the algorithm, one must express Q(c|ĉℓ−1) in a form convenient for maximization.
Algorithm 1: Complete RLS algorithm.
Algorithm 2: Complete Hybrid algorithm.
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CEO of Professional Science Editing for Scientists @ prosciediting.com