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16 Dec 2013: Our tests suite takes nine minutes to run (distributed across 30-40 machines). ... Build for Change. Communicate Clearly. Test Continuously, Test Everything- problem understanding, user behaviour assumptions, code, integration.

16 Dec 2013: Check in Everything (!) you need to create, install, run and test: code, tests, database scripts, build and deployments scripts, etc. ... http://dannorth.net/introducing-bdd/. • “Behaviour” is a better word than “test” - different focus- Unit

5 Oct 2013: the corresponding backward test channel [5, 15, 63]. This is a fictitious channel. ... test channel conditional distribution, and both of them are assumed to have memory.

16 Dec 2013: results into account, we develop and test several algorithms based on these. ... We discuss. and test these approaches for demodulation and CDMA detection in flat.

16 Dec 2013: Design a test plan for the project, specifying types of tests, including their purpose and examples. ... 4. Why wasn’t this mistake spotted by in testing? – The app submission is a manual process and there are no tests to check the correctness of the

16 Dec 2013: Acceptance tests may test functionality (functional acceptance tested) but may also test other qualities of the system such as capacity, usability, security, modifiability, availability, etc. • ... 16. 16. 2012 Elena PunskayaCambridge University

15 Aug 2013: Forthis example the test error was 0.0309 and an average of6.18 kernels were used. ... Method Test Error # KernelsSVM [6] 8.04 142.8RVM [7, 8] 7.46 39.0TD-SMC 7.18 25.29.

5 Aug 2013: Fig. 2. Left: the input test image with features of different size andnature. ... Figure 2 shows the 15detected maxima on the test image. All the detected locations.

5 Aug 2013: the50 images in our test set, be-ginning again when all images had been used. ... 3.3. Instructions. Prior to performing the psychovisual tests, all subjects wereissued with a set of instructions.

5 Oct 2013: Set R0 = Y. In Step k = 1, 2,. 1 Compute inner product of each column with Rk12 Pick columns whose test statistic crosses threshold τ. ... 3 Rk = Rk1 Fitk4 Complexity O (ML log M ). 9 / 21. Performance. How many sections are decoded correctly? Test

5 Aug 2013: So both training and test database contain520 images. We have made this database available online3. ... Classification and browsing experimentsare conducted on the test database after transformation withthe SDM.

15 Aug 2013: The left side of Figure1 shows the test error as a function of the number of samplesN. ... For this example the test error was0.0309 and an average of 6.18 kernels were used.

5 Aug 2013: One (“auxiliary”) is above and somewhat in front ofthe other (“reference/test”), the difference in elevation being about 15. ... We also ran comparable tests using fixed thresholds– e.g. 5 pixels from the epipolar intersection, irrespective of

5 Aug 2013: The second experiment tests the meth-ods on locally varying and anisotropic fractal dimension. ... Fi-nally, a classification problem is used to test how well eachmethod can segment data based purely on the directionalityof fractal dimension.

5 Aug 2013: I In our tests, we set this threshold to be 0.4, with the unconstrainedSIFT initial matches as the baseline. ... Experimental results. Results. I We also performed tests on the ZuBud building database.

5 Aug 2013: DT CWT in 2-D. Test Image and Colour Palette for Complex Coefficients. ... Rotation-Invariant Feature Matching. Correlation plots for two simple images. Test image (a).

5 Aug 2013: Test image (a). 0 90 180 270 360. 0.5. 0. 0.5. ... Correlation plots for more complicated images. Test image (c). 0 90 180 270 360.

5 Aug 2013: Preliminary tests on someclassic building scene images show that the method works well. ... The second step isto find the putative correspondences of the features betweenthe template and the test image.

5 Aug 2013: viewpoints of the test objects while the computationalload is only increased by about 25% over baseline SIFT. ... To test our al-gorithm, we performed experiments to compare the algorithmwith baseline SIFT and spectral graph matching [6].

5 Aug 2013: The image area covered by. Test image (a). 0 90 180 270 360. ... 0.5. 0. 0.5. 1. Rotation (degrees). Test image (c). 0 90 180 270 360.

5 Aug 2013: 1. 0. 1. 2. 3. Fig. 3. Training data (500 points) for the ‘zig-zag’ test example,shown as ‘’ and ‘’ for points above and below the decisionboundary (dashed line) respectively. ... To test our systems, we randomly chose 400samples as a

5 Aug 2013: In this setting,robustness to shifts allows sparser sampling of the test features. ... overlapping of test feature samples which can be exploitedfor a modest computational speed-up.

5 Aug 2013: We briefly compareour method against SIFT for a test target in section 5, andconclude in section 6 with a discussion of the results and thenext steps for our research. ... We use the same setup to test the SIFTmethod2, and compare the two methods’

5 Aug 2013: The ca-pacities of a set of test images (each of 256 256 pixels)were measured and the results are summarised in the table 1.We can see that the CWT ... Table 1: Theoretical (a) and empirical (b) capacities in kbitsof the set of 256 256 test images.

15 Aug 2013: In Proc. Applications of heavy tailed distributions in economics, engineering and statistics, June 1999.

5 Oct 2013: the test statistics for the second step.The decoder again selects the columns for which this statisticcrosses the threshold. ... The analysis of the algorithm is challenging due to thedependence between the test statistics used in each step.

17 Dec 2013: 0.4019, 0.4823, 0.5787, 0.6944, 0.8333. Again, compute the mean-squared quantisation error for the two test signals.

5 Aug 2013: We test the algorithm on 3 examples: a simplering, the cameraman image and a 3D microscope dataset; andshow that good results can be obtained. ... In figure 2, we show a deconvolution experiment on thestandard 2D test image Cameraman, which has been

5 Aug 2013: Figure 2 illustrates a test of this by plotting PSNR (=10 log10(255. ... For these tests, we took the upper curve of fig. 3 andat every third point introduced a 2-D circularly symmetriccomplex quantizer into the loop in place of the centre

5 Aug 2013: 10). These can be pictured in terms of the test channel from to. ... Equation (9) describes the sequence of input distributions to. this test channel and (10) specifies the test channel.

5 Aug 2013: For comparative purposes, we performed a series of exper-iments on 2 standard test images (Cameraman, House). ... ISNR(x(n)) = 10 log10(‖y x‖2. ‖x(n) x‖2) (20). For each test case, we used the same initial estimate as [6],which was obtained using

16 Dec 2013: 3. (a) describe how you would conduct a usability test? (b) what metrics would you use and how would you measure them?

5 Aug 2013: An estimateof the noise-to-signal power ratio is computed in advanceby spectral ratio techniques and made available to both thealgorithms under test. ... Hence:. F̂X,Y = D1X,Y BX,Y. In our test problem, eachDX,Y matrix is 584 584.

5 Aug 2013: We typically considerX as the “reference” image and Y as the “test” image. ... Thus,the resampling only applies when the “test” image producesfewer interest points than half the number produced by the“reference” image.

24 Oct 2013: The third test set [8] selectedbreaks this trend as it requires speaker recognition, usingprocessed recordings of spoken Japanese vowels. ... Effective dimensionality. Sepa. rabi. lity. (d) Quadrotor behaviours. Fig. 4. Geometric separability of the

5 Aug 2013: 4.1. Experiment settings. For comparative purposes, we performed the experiments on thestandard test image, Cameraman. ... ISNR(x(n)) = 10 log10(‖yx‖2. ‖x(n)x‖2). For each test case, we used.

5 Oct 2013: Example: GNP vs Money Supply [Geweke ’82]. Delay. Test Ch. Test Ch.

15 Aug 2013: To highlight the potential applications of such methods, we provide examples usingtwo of the most distinctive time–frequency surfaces—speech and music signals—as well asstandard test functions from the wavelet ... To test the ability of the Gabor

16 Dec 2013: Implement a prototype. • Test each use case with each user type and iterate- do not ignore the minority in favour of the majority- note areas where people have trouble. ... center. This scenario will be elaborated upon for the test case used with our

5 Aug 2013: wkm. αmAm. n. αnbn =m,n. αmαn (Am? Bn). (4). Here, each weighted channel of the template is matchedwith all the weighted channels of the test image. ... wkm. γmAmbm =m. γm (Am? Bm) , (5). so that, for example, only the red channel of the template

5 Aug 2013: DT CWT in 2-D. Test Image and Colour Palette for Complex Coefficients. ... Application 1: Registration. Tests of registration with 3D CT scans. (a) Venous phase (b) Delay phase.

5 Aug 2013: Test Image and Colour Palette for Complex Coefficients. Real part. Imag.

16 Dec 2013: A test is designed which candetect the condition, if it is present, with 95% probability. ... Since 62 pass the me-chanical test, then the number taking branchb = 6235 = 27.

16 Dec 2013: x : f (x) = 0}. and test each point to find the minima. •

5 Aug 2013: A single shot/streamer line was selected from thedata volume to test the complex wavelet least-squares migrationalgorithm in 2 dimensions.

5 Aug 2013: DWT operator completely fails tocope with misalignment due to its excessive shift variance.For our test data of typical urban and vegetation images,93% of the ILP match attempts at

15 Aug 2013: Many possible observation models are available forthis dynamical model, and we have explored several.In order to test a challenging non-Gaussian case, weadopt here a Poisson target model with independentPoisson

5 Aug 2013: used to test the classifier. A common complaint against supervised approaches is that,. ... test, together with those of the human operators. Around the 95% true positive region,.

5 Aug 2013: Consider Keypoint 12,corresponding to the nested circles of the test phantom introduced in[1] and illustrated in Figure (2).

5 Aug 2013: Tests on a reasonably large, real synthetic aperturesonar imagery dataset show that the ripple suppression methodpreserves detection performance of the matched filter on non-rippled data and significantly increases the detection