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Exact(6)
Neural networks trained by the proposed method are robust against stochastic uncertainties.
The local features obtained by the SIFT method are robust to image scale, rotation, changes in illumination, noise and occlusion.
Nevertheless, we can see that all of the configurations of the proposed method are robust to requantization, inversion, additive noise, and MP3 codecs, which is comparable with the robustness of other audio data hiding techniques [30,31].
The verifications based on both pseudo-experimental and real experimental data have shown that the present developed model and method are robust and can uniformly describe various adhesive failures without need to consider selection of appropriate CZM for different types of fracture problems.
Finally, the retrieval results obtained by our method are robust with regard to the number of modules and submodules.
Critical to our method are robust estimates of differential methylation (DM) at individual CpG sites derived from limma[ 43], arguably the most widely used tool for microarray analysis.
Similar(54)
This method is robust in noisy situations.
Our method is robust, automatic and efficient.
Using spatial similarity, the proposed method was robust against shadows.
This method is robust for any lips shape.
Hence, the proposed method is robust to content-preserving operations.
Related(16)
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