Search alternatives:
left optimization » lead optimization (Expand Search), yet optimization (Expand Search), led optimization (Expand Search)
loop optimization » codon optimization (Expand Search), wolf optimization (Expand Search), lead optimization (Expand Search)
binary model » final model (Expand Search), injury model (Expand Search), tiny model (Expand Search)
image loop » image 1_look (Expand Search)
left optimization » lead optimization (Expand Search), yet optimization (Expand Search), led optimization (Expand Search)
loop optimization » codon optimization (Expand Search), wolf optimization (Expand Search), lead optimization (Expand Search)
binary model » final model (Expand Search), injury model (Expand Search), tiny model (Expand Search)
image loop » image 1_look (Expand Search)
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Flow diagram of the automatic animal detection and background reconstruction.
Published 2020“…If the identical blob that was detected in panel J (bottom) is found in any of the new subtracted binary images (cyan arrow), the animal is considered as having left its original position, and the algorithm continues. …”
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Thesis-RAMIS-Figs_Slides
Published 2024“…Importantly, this strategy locates samples adaptively on the transition between facies which improves the performance of conventional \emph{<i>MPS</i>} algorithms. In conclusion, this work shows that preferential sampling can contribute in \emph{<i>MPS</i>} even at very small sampling regimes and, as a corollary, demonstrates that prior models (obtained form a training image) can be used effectively not only to simulate non-sensed variables of the field, but to decide where to measure next.…”