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A homography model, estimated by global motion estimation, is rather used in [65] for interview prediction, showing significant improvement in the SI quality.
And the important thing to design the motion estimation is power optimization, which is achieved by carefully designing motion estimator.
However, it is not easy to estimate the real motion of objects and background, because motion estimation is regarded as an underdetermined problem.
Motion estimation is performed without knowledge of the original Wyner-Ziv (WZ) frame: it assumes linear motion.
Block matching motion estimation is the heart of video coding system.
Motion estimation is an important component in power-consumption of video codec.
In this paper, the design of hardware architecture for a bio-inspired neural model for motion estimation is presented.
The problem of high precision motion control of remotely operated vehicles (ROVs) in the proximity of the seabed through vision-based motion estimation is addressed in this paper.
A real time application in video motion estimation is also considered by authors to test the efficiency of the SIMBO variants.
The motion estimation is based on a strongly localized bio-inspired connectionist model with a particular adaptation of spatio-temporal Gabor-like filtering.
In this paper the problem of high-precision motion control of remotely operated vehicles (ROVs) in the proximity of the seabed through vision-based motion estimation is addressed.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com