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The highest accuracy classification (83.2%) used both biophysical and spectral data.
Some features are presented for high accuracy classification of noisy signals with different noise levels without the requirement of de-noising preprocess.
Next we considered whether any factors affected our more stringent accuracy classification, that is, being correct on both the detection and location tasks (DL).
The performance of the proposed system in terms of tracking accuracy, classification efficiency and time expenses is tested and discussed with synthetic and real input-scene sequences.
Similarly, an interactions-based accuracy classification method [44] has been shown to provide a superior assessment of docking pose quality compared to simple RMS deviations from crystal structure poses.
For the location task, using the more liberal accuracy classification, that is, both DL and nDL responses, we found that two factors had an effect on likelihood to respond correctly.
Similar(50)
A number of researchers employed neural network to achieve high accuracy classifications in both academia and industrial fields.
Our results showed that very dense time series allowed for very high accuracy classifications (>90%) of small scale vegetation types.
Huge time consumption is the major reason of why some theoretically high-accuracy classification algorithms could not get out of the laboratory.
Though the two works reported better accuracy in classification, these classifications are computationally rigorous.
Ninety-eight percent accuracy in classification has been achieved.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com