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20 Feb 2018: The corpus was segmented into a “trainingsub-corpus” and a “test sub-corpus,” which are each com-posed of an equal number of dialogs, the same mix of worderror rates, and ... increase, the average reward per turn decreases as expected,and in

20 Feb 2018: 5. Perceptual EvaluationA direct comparison between F0 conversion methods was facil-itated using a three-way preference test. ... The same test was then conducted using converted neutralutterances generated by our conversion system.

20 Feb 2018: occur simultaneously in the training and test partitions. In contrast, in our evaluation.

13 Mar 2018: This requires a limited effort incoarsely labelling a small subset of the test data. ... 6.1 Quantitative EvaluationFig. 5 illustrates change detection performance over the two test datasets.

13 Mar 2018: We also used dropout at test time [13] but observed verysimilar performance gain without it. ... However, dropout at. test time [13] makes the network robust to out-of-domaindata.

13 Mar 2018: The parameters for both methods are setby testing the classification performance on a test setof 5000 images. ... In a first approach,the edge and colour cost terms are computed for a numberof test images.

13 Mar 2018: State-of-the-art commercial system FaceIt by Identix[12] (the best performing software in the most recentFace Recognition Vendor Test [13]),. • ... KLD) [14]. In all tests, both training data for each person in the gallery,as well as test data,

13 Mar 2018: Iden. tific. atio. n ra. te. Effect of the dimension on the test set. ... Anindependent illumination set with both training and test sets was exploited for the val-idation.

13 Mar 2018: The running of tests consisting of all possible combina-tions of all trackers on all test sequences would take a pro-hibitive amount of time to complete. ... In order to test the validity of such a setup, weperformed tests using the complete tracking

13 Mar 2018: At test time we also normalize the quaternion orienta-tion vector to unit length. ... This noveldataset provides data to train and test pose regression algo-rithms in a large scale outdoor urban setting.

13 Mar 2018: test time, the image is extended toensure a smooth estimate of the semantic textons near theborder. ... Figure 6. MSRC segmentation results. Above: Segmentations on test images using semantic texton forests.

20 Feb 2018: Table 1 shows the weighted F-1 scores computedon the test set for each label.

20 Feb 2018: Thanks to Karl Weilheimer and Matt Stuttle for their assistance with the tests and for helpful comments on transcription conventions.

13 Mar 2018: single other – we used 9 randomly selected training/test combinations, see Figure 7. ... places low demands on storage space. 17. Table 2Evaluation results:The mean recognition rate and its standard deviation across differenttraining/test illuminations

13 Mar 2018: M}. For a test image xt, the task is to predictyt A, i.e. ... The vali-dation set and the test set contain 2104 and 2967 imagesrespectively.

13 Mar 2018: We test the performance of SegNet on outdoorRGB scenes from CamVid, KITTI and indoor scenes fromthe NYU dataset. ... Features based on appearance[32], SfM and appearance [2, 36, 20] have been explored forthe CamVid test.

13 Mar 2018: We capture six test scenes with the same five objects. Eachtest scene has 400 500 frames containing multiple objects with different back-grounds/clutter and poses.Scenario 4: This scenario tests ... Recall. Pre. cis. ion. LineModSupp. SIterative(Edge).

13 Mar 2018: Quantitative test was done on unsegmented KTH datasetusing the classifiers learnt in the previous experiment. ... In test set-up, we used unsegmentedKTH data for incremental training (i.e.

20 Feb 2018: Dataset Train Dev Test #SlotsRestaurants 1612 506 1117 4. Tourist Information 1600 439 225 9Table 5: Number of dialogues in the dataset splits usedfor the Dialogue State Tracking experiments.

13 Mar 2018: This is achieved by sampling the network with randomly droppedout units at test time. ... Table 3: Pascal VOC12 [9] test results evaluated from the online evaluation server.