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The proposed system deliberately selects constituent weak classifiers that are expected to show good performance in real detection environments.
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In this case, for real system design, we evaluate the performance in terms of detection probability for ideal energy detection method, transmitter-independent energy detection method, and transmitter/receiver-cooperated energy detection method.
Non-diluted human blood plasma has been used for real sample application where electrode showed excellent performance in urea detection.
The open questions and key challenges along the way for rational designing on-site probe based on ICP nanoparticles with high sensitivity, selectivity and reliability are also discussed and illustrated, which would inspire future investigations on the development of ICPs-based probes with striking analytical performance for real sample detection in a simple and convenient fashion.
Experimental results on simulated and real multispectral remote sensing data have shown that the proposed method has excellent performance in ship detection.
Similar to EPSC detection, our method achieved excellent performance in IPSC detection across datasets.
Third, Cu-based sensors offer competitive performance in electrochemical detection.
Our system shows robust performance in traffic sign detection, and experiments on real-world scenes confirmed its properties.
Our detector gives better performance in this simple detection task.
In this paper, the performance of a blind detector that employs the symmetry property of the cyclic autocorrelation function to perform signal detection in real channel conditions is tested.
The cough detection task is also very essential in real world cough detection problem.
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