Exact(58)
The likelihood evaluation relying on occupancy and color information is computed on local neighborhoods, thus dramatically decreasing the computation load of the overall algorithm.
These points will not be computed in the subsequent iterations, and thus the computation load is reduced, especially for the long contours.
However, the computation load cannot be neglected.
That way the computation load can be kept relatively small.
The computation load becomes heavy when the size of is large.
Firstly, it avoids exhaustive search and greatly reduces the computation load [17].
Considering the computation load, we can design a variable step-length searching method.
An approximate and simplified architecture is proposed to reduce the computation load.
A simplified implementing architecture is presented to reduce the computation load.
Similar(2)
It informs the QoD Engine about the computation loads at runtime in order to automatically tune the QoD constraints.
To reduce the computation loading, a bandlimited CCS is presented in this paper on the basis of subband filtering approach.
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