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State of the art.
If something is state of the art, it is the most up-to-date model incorporating the latest and best technology.
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The results provide a pathway towards practical use of the ET analysis method in state of the art performance-based design and probabilistic estimation of losses.
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Their expertise includes current methods in state-of-the-art technologies.
We describe the different algorithmic steps in detail and evaluate the online method against state-of-the-art peak extraction methods.
In Section 6, we perform a detailed comparison of the DG3PD method to state-of-the-art decomposition approaches.
The demonstrate the efficiency of the method compared to state-of-the-art methods, and also demonstrate an application in mining composite transcription factor binding sites.
Last, we give a performance evaluation by comparing the proposed methods to state-of-the-art methods in Section 4.3.
Our proposed method is compared against state-of-the-art pose graph optimisation algorithms in 2 and 3 dimensions.
Our method shows consistent improvements over state-of-the-art methods.
Our method was further compared with state-of-the-art methods on the same datasets.
The experiments illustrate that the proposed method outperforms the state-of-the-art methods in 3D localization and tracking performance.
In order to examine the performance of our proposed method, three state-of-the-art feature selection methods, mIMR, mRMR and CMIM, are used to compare with RESI.
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