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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: 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: 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: 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: 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: 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.

15 Jun 2018: Thisconsists of about 1M words of acoustic transcription. Eightmeetingswere excluded from the training set and used as the developmentand test sets. ... Confusion network decoding canbe ap-plied on the rescored lattices and additional 0.3-0.4% WER

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.

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: The six test sets were created by randomly. 8 KIM et al.: GROWING A TREE FROM DECISION REGIONS OF A BOOSTING CLASSIFIER. ... Caltech bg datasetMPEG-7 f ace data. BANCA f ace set. MITCMU f ace test set.

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: In [14], error is computed using a“leave-one-out” test rather than with completely new testdata. ... A leave-one-out test for gaze-tracking data with theS3GP gives an error of 0.68.

13 Mar 2018: 0. 0.1. 0.2. 0.3. 0.4. 0.5. Test index. Rel. ativ. e re. ... The tests are shown in the order of increasing raw data performance foreasier visualization.

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.

13 Mar 2018: The class that exhibits the maximum frequency in the histogram is as-signed to the test video. ... The train/test split is around 50% and the videos arechosen as specified in [17].

13 Mar 2018: It seems that some form of single stage regressionmight be more powerful, both for dealing with the rangeof variation of test examples, and for correctly modellingstatistical variability. ... Forefficiency, this test is made only every M frames (in

20 Feb 2018: NCE is thus a suitable metricfor evaluating the accuracy of probability estimates given a setof hypotheses, but it does not necessarily test the overall cor-rectness of the output.

13 Mar 2018: b) Humanbody segments from the baseline and Factored ConvNet (B and F) on example images from Unite thePeople S31 test set. ... a) YouTube Pose (b) Unite the People S31. Figure 7: Qualitative examples on Youtube Pose videos and Unite the people S31 test