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For example, Figure 1 shows the relevant MBs for this early SKIP mode detection approach.
We propose a fast skip mode detection approach by exploiting surrounding skip patterns, rate distortion (RD) cost and coded block pattern (CBP).
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The kernel density approach for mode detection is adopted and improved for operating mode detection.
For online mode detection, the model-based clustering discriminant analysis (MclustDA) approach is incorporated with some a priori knowledge of the system.
Although this approach achieves considerable speed boost with early SKIP mode detection, we find there is still much room for improvement in SKIP mode detection for CGS.
These were too scarce to be seen under the microscope – only the more sensitive DNA detection approach picked them up.
Figure 1 Relevant predictors for early skip mode detection.
Consider a detector that has POP mode detection.
POP mode detection allows you to be warned of this type of radar.
Fig. 1 Taxonomy of malware detection approaches.
Two alternative event detection approaches are studied.
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