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13 Mar 2018: Givena test image with its feature vector xt, its score for attributeam is given by ϕ(bTm, xt). ... Absolute Classification: This refers to the task of as-signing a test image to its correct class.

16 Feb 2008: 716.4 Translation examples for the EPPS Eval05 test set : ASR 1-best and. ... BLEU is defined over all the sentences in the test set i.e.

13 Mar 2018: 9. Adding more parts helps performance on the test data up to a. ... effect on the RP EER (up to 100N percent for N test images).

21 Dec 2005: also see [27]). In AFR tests, such methods are usually outperformed by meth-. ... the data as test input. In all tests, both training data for each person in the gallery,.

13 Mar 2018: also see [27]). In AFR tests, such methods are usually outperformed by meth-. ... the data as test input. In all tests, both training data for each person in the gallery,.

28 Jun 2021: 3. We use easily obtained 2D annotations in training, and none at test time. ... or rely heavily on input 2Dkeypoints or video at test-time [31, 28].

13 Mar 2018: Figure 7. Sample of sparse reconstruction output. Top: a long reconstructed section; middle: close-. ... detection system and test it more extensively, comparing. the inspection performance between manual, fully-.

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: Figure 1. A building façade (left), the edgels output from Canny (middle) and the resulting straightline-segments (right). ... 5 EvaluationTo test this system, a database was constructed from photographs of all the buildings in the main shoppingstreet

13 Mar 2018: InAFR tests, such methods are usually outperformed by methodsfrom the third class: view-based techniques e.g. ... These were used for neither gallery data nor test inputfor the evaluation reported in this section.

13 Mar 2018: Figure 2: Appearance variation of hand regions. Shown. are cropped hand regions from test sequences. ... pair from NCC to CM due to motion blur, middle pair from CM.

13 Mar 2018: We obtained propagated labels for all the images in thetrain, test and validation datasets, however we use only thelabels in the training dataset in the experiments describedhere. ... or Hand labels. The graph on the right shows class accuracy and IoU

25 May 2006: WB (t) =. π |φs2(t d̃k) φs1(t)|. π. n. (25). We test the simple strategy of Equation 25, where n determines the severity of the deweighting.WPS variants with n ... We test two families of deformation estimators. The first is an example of

13 Mar 2018: The imageswere randomlyandequallypartitioned intoa trainanda test set.Thetrainsetof161imageshad323frontalfacesand192profilefaces and the test set had 271 frontal and 171 profile faces. ... 184 T.-K. Kim and R. Cipolla. Fig. 17 Example tracking results on

13 Mar 2018: 2 Hernández et al. test our hypothesis. Therefore the problem of detecting shadows becomes moredifficult. ... 3 top. Thenormalized images ci‖c‖ in the middle of Fig. 3 allow the algorithm to easily detect.

13 Mar 2018: correlations chosen from the list is performed to categorize. a new test video. ... scenarios. Leave-one-out cross-validation was performed. to test the proposed method, i.e.

13 Mar 2018: Illumination conditions were mildly different in training and test sequences,see Figures 8 and 9. ... 9] B. Kepenekci, Face recognition using gabor wavelet transform., Ph.D. thesis,The Middle East Technical University (2001).

12 Jul 2005: Illumination conditions were mildly different in training and test sequences,see Figures 8 and 9. ... 9] B. Kepenekci, Face recognition using gabor wavelet transform., Ph.D. thesis,The Middle East Technical University (2001).

13 Mar 2018: pression is minimised (middle). An optimal short tree is built on theminimum expression (right). ... 8(left) and Fig. 9(left). The six test sets werecreated by randomly perturbing the train sets.

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

13 Mar 2018: We used 18 randomlyselected training/test combinations of the sequences forreporting identification rates. ... The test recognition rates changed byless than 1 percent for all of the different trials of randompartitioning.

13 Mar 2018: The results are shown in the top row of Table 1 and the middle row of Fig. ... Fromtop to bottom: test image, ground truth, motion and structure inferred segmentation,and appearance inferred segmentation.

13 Mar 2018: Middle) The clusters of region trajectories computed with our algorithm are represented with differentshaded colours (some colours may be repeated). ... 1. To limit the computational load we con-sider the first 100 frames only.Our main purpose is to test

13 Mar 2018: We used 18 randomlyselected training/test combinations of the sequences forreporting identification rates. ... The test recognition rates changed byless than 1 percent for all of the different trials of randompartitioning.

13 Mar 2018: 2. Fig. 1. SegNet predictions on urban and highway scene test samples from the wild. ... 1). Some example test resultsproduced on randomly sampled road scene images from Googleare shown in Fig.

28 Jun 2021: 3. We use easily obtained 2D annotations in training, and none at test time. ... or rely heavily on input 2Dkeypoints or video at test-time [31, 28].

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: Figure 7. Sample of sparse reconstruction output. Top: a long reconstructed section; middle: close-. ... detection system and test it more extensively, comparing. the inspection performance between manual, fully-.

13 Mar 2018: Figure 1. A building façade (left), the edgels output from Canny (middle) and the resulting straightline-segments (right). ... 5 EvaluationTo test this system, a database was constructed from photographs of all the buildings in the main shoppingstreet

22 Jun 2006: The phantom included spheres of 1.5 cm, 1.0 cm and 0.5 cm diameter, in order to test theresolution of the algorithms. ... For this reason, it is not possible to use Field simulations created in thisway to test the frequency-based methods of attenuation

13 Mar 2018: 1.0} (1), and =0.07. |S |= 6 test scales were chosen automatically to cover the scale range in the trainingdata. ... Left: categorization performance. Middle: detectionperformance, with comparison to Opelt et al.

13 Mar 2018: 9. Adding more parts helps performance on the test data up to a. ... effect on the RP EER (up to 100N percent for N test images).

13 Mar 2018: We used 18 randomlyselected training/test combinations of the sequences forreporting identification rates. ... The test recognition rates changed byless than 1 percent for all of the different trials of randompartitioning.

13 Mar 2018: avoid bias), resulting in a total of 600 pairwise compar-isons per preference test. ... Scores shown as percentages of all votes for: (left) all emotions, (middle)neutral, and (right) angry.

13 Mar 2018: avoid bias), resulting in a total of 600 pairwise compar-isons per preference test. ... Scores shown as percentages of all votes for: (left) all emotions, (middle)neutral, and (right) angry.

13 Mar 2018: The imageswere randomlyandequallypartitioned intoa trainanda test set.Thetrainsetof161imageshad323frontalfacesand192profilefaces and the test set had 271 frontal and 171 profile faces. ... 184 T.-K. Kim and R. Cipolla. Fig. 17 Example tracking results on

13 Mar 2018: As closely as pos-sible, we use the same training and test sets. ... We test each class individually, pairedwith an equal number of background test images.

13 Mar 2018: The results are shown in the top row of Table 1 and the middle row of Fig. ... Fromtop to bottom: test image, ground truth, motion and structure inferred segmentation,and appearance inferred segmentation.

13 Mar 2018: because highlights are very strong and localized, so just a simplesensor saturation test is enough to find them, i.e., highlight 254. ... The next experiment was designed to test thisimprovement by performing a light estimation over K imageswhere the

11 Sep 2019: How-ever, these are not feed-forward at test time and requireoptimization to determine the MAP labels. ... We report all the threemeasures of performance at this point on the held-out Cam-Vid test set.

13 Mar 2018: Our work can be seen as a type of middle ground be-tween the domains of motion segmentation and multi-bodyfactorization. ... These would in turn preventthe “spawning” of new entity hypotheses in the middle ofthe scene.

13 Mar 2018: avoid bias), resulting in a total of 600 pairwise compar-isons per preference test. ... Scores shown as percentages of all votes for: (left) all emotions, (middle)neutral, and (right) angry.

8 Aug 2005: We performed 25 recognition tests, using each database for training and testing it against all the others.For each person in a database we collected a data set consisting of ... 10] B. Kepenekci. Face Recognition Using Gabor Wavelet Transform.PhD thesis,

16 Nov 2007: 8.1.1 Training and Test Corpora 102. 8.1.2 System configurations 103. 8.2 Initial Experiments 106. ... ments. A summary of the history of NIST’s benchmark tests are given in [91].

9 Aug 2005: cast News Benchmark Test Evaluation, the general procedures used are described and previous. ... Test Evaluation, four sites (BBN, MITRE, SPRACH and SRI) participated and submitted their.

13 Mar 2018: 1.0} (1), and =0.07. |S |= 6 test scales were chosen automatically to cover the scale range in the trainingdata. ... Left: categorization performance. Middle: detectionperformance, with comparison to Opelt et al.

12 Aug 2019: Average 62.8 64.4 69.5. Table 1: Accuracy of OJA onBADJA test sequences. ... Middle: Themodel has never seen an elephant, so assumes the trunk is the tail.

16 Feb 2008: exponential of the cross entropy of the language model on the test set. ... using the posterior distribution with the goal of improving phrase coverage on test.

16 Nov 2007: representation 103. 6.5 Synchronous stream system with confidence weighting 107. 6.6 Results using GMM features on WSJ corpus and CSRNAB hub 1 test set 108. ... diagonal transforms 127. 8.4 Experiments using constrained MLLR transforms for WSJ test

13 Mar 2018: Our test-frames, code for evaluating them, and per-frame scores areonline, with the aim of encouraging more meaningfulalgorithm comparisons, when possible. ... 7.2 Qualitative Tests of Cloth and Face. For the third experiment shown here, a model wearing