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When the TR is 30 fps, the gait recognition accuracy degrades as the SR decreases, but the degradation is moderate during verification.
Estimation accuracy degrades close to borders of the frame because of signal discontinuity and spectral leakage.
In the absence of historical data (past observations), it is reported that prediction accuracy degrades dramatically [22].
The accuracy degrades when more instruments are considered, but meaningful estimates can be obtained for up to five simultaneous instruments.
Results show that the approximation perfectly fits the empirical results at low SNR values; however, the approximation accuracy degrades as SNR increases.
Results show a perfect match between the empirical results and the analytical approximation at low SNR values, however, approximation accuracy degrades as SNR increases (ρ>−2 dB).
Similar(41)
For example, when TR is 1 fps, recognition accuracy degrade drastically as SR becomes low.
As observed, the detection accuracy degraded as the data size increased in all three cases, as the increasing data size leads to decreasing detection efficiency.
When is small and is approaching zero, the estimation accuracy of degrades.
For the TR, the gait recognition accuracy generally degrades as the TR decreases, but there are some exceptions.
We can see from the table that FJLT hashing is obviously sensitive to rotation attacks and thus its identification accuracy greatly degrades with the increase of rotation degree.
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