Sentence examples for test scenes from inspiring English sources

Table 4 Training and test scenes Scene's SI class Training scene Test scene Test scene label High party_act2 party_act1 VS1 party_act3 VS2 Party_act4 VS3 Medium office_act1 cLowsroffice_act24 classroffice_act25 classroffice_act26 office_act2 VS7 Loffice_act2ct2 office_act2 VS8 classroffice_act29.

Using the fairness ratio obtained from the training scenes, the fairness based algorithm explained in Section Fairness-based CID allocation for the Test Set will be used to allocate the VSN nodes' CID for all test scenes.

Figure 5 shows the relative amount of spatial and temporal information for the selected test scenes.

The smoothness and correctness of this effect will be judged in a few test scenes.

In Figure 10a, one of the test scenes with objects from five different classes is presented.

Correspondingly, Table 4 shows the training scenes and their corresponding test scenes.

In this regard, Table 10 shows the Pnet, Pavg and STD(Pi) of the three algorithms for all test scenes.

Figure 15 Comparison of the P net, P avg, and STD(P i ) values obtained from all test scenes.

Enhanced Local Tone Mapping (ELTM) is a flexible tone mapping operator designed to provide a good global and local contrast simultaneously over various test scenes.

The fairness ratio obtained by the proposed optimization-based approach is then used in the proposed fairness-based encoder complexity and bitrate allocation algorithm for the test scenes.

In this paper we provide a comparative study of a number of these techniques, all implemented in a single system and run on the same test scenes and on the same computer.