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The proposed process achieved high detection performance with less error rate of 0.42% in detecting QRS complex.
A strong classifier is a classifier which is supposed to have high detection performance.
We expect that, even without them, the combination of GMMs and SVMs will have high detection performance.
The human detection is then guided by the candidate windows, offering high detection performance even when the detection task terminates prior to completion.
In practice when the model parameters are unknown, two Generalized Likelihood Ratio Tests are designed to deal with this difficulty such that they can meet a prescribed false alarm probability while ensuring a high detection performance.
It is conjectured that the high detection performance is due to high electron-mobility of F16CuPc, the large band edge offset between D/A molecules as well reasonable design of the diode structure.
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The results show very high detection performances for each class, and also confirm the consistency of the proposed method in the repeating process.
To achieve the highest detection performance, there is an optimum choice of the sensor number.
Experimental results show that a cascade classifier using weak classifiers selected by the proposed method has a higher detection performance.
While these methods achieve higher detection performance, the weight update is heuristic, making it difficult to predict performance prior to in-field use.
In the Caltech Faces, the AdaBoost HL cascade shows higher detection performance than our MS-EGM, which wins against the AdaBoost HL cascade, in terms of process speed.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com