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Sanin et al. [1] classified the moving shadow detection methods under various categories.
Theoretical curves are acquired to compare the characteristics for individual energy detection methods under various situations.
A simulation study is carried out to evaluate the performance of the multivariate outlier detection methods under various conditions.
A simulation study is conducted to evaluate the performance of the multivariate outlier detection methods under various conditions.
Performance theoretical curves are acquired to compare the characteristics for individual energy detection methods under various scenarios.
We tested the performance of the sparse methods under various degrees of light calibration error on the Caesar dataset.
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Figure 5 Classification accuracy of the LLDC method under various k LDV on ICPR 2012 dataset.
From their research, the MLH method performed better than the PRH method under various added noise experiments while maintaining accuracy.
Figure 6 Classification accuracy of the LLDC method under various k LDV on ICIP 2013 training dataset.
Self-catalyzed GaAs NWs were grown on a (111 Si substrate by MBE-VLS method under various arsenic fluxes.
Average error rate performances for the proposed method under various levels of traffic load are given in Fig. 7.
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methods under saturated
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