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Tesseract Tools for Android is a set of Android APIs and build files for the Tesseract OCR and Leptonica image processing libraries . The source code for these ...

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for a Here, pis a suitable bounded function (usually one assumes that pis symmetric around 0, p(0) = 1, and that p ( 2 ) decreases monotonely to 0 as z --+ CQ), and 0 < 6 < 1 is a suitable constant The S-estimate is now defined to be the 8 minimizing 8(0)If p and 6 are properly chosen (the proper choice depends on the distribution of the carrier X , which is awkward), the breakdown point asymptotically approaches This estimate has the usual nP1/ convergence rate, with high efficiency at the central model, and there seem to be reasonably efficient algorithms However, with non-convex minimization, like here, one usually runs into the problem of getting stuck in local minima Moreover, Davies (1993, Section 16) points out an inherent instability of S-estimators; in my opinion, any such instability disqualifies an estimate from being called robust.



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In fact, there are no known high breakdown point estimators of regression that are demonstrably stable; I think that for the time being they should be classified just as that, namely, as high breakdown point approaches rather than as robust methods Some authors have made unqualified, sweeping claims that their favorite estimates have a breakdown point approaching in large samples Such claims may apply to random carriers, but do not hold in designed situations For example, in a typical case occurring in optimal designs, the observations sit on the d corners of a ( d - 1)dimensional simplex, with rn observations at each corner In this case, the hat matrix is balanced: all self-influences are hi = l / m , and there are no high leverage points.





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Add the Google Play Services dependencies and build the starter app. Now you're ready to open the starter project. Select the ocr -reader-start directory from your sample code download (File > Open > ocr -codelab/ ocr -reader-start ). Add the Google Play Services dependency to the app.

, the DAIS working group seeks to promote OGSA compliant standards for Grid database services, the Grid Economic Services Architecture Working Group (GESA-WG) [63] seeks to de ne standards for charging Grid services, the Resource Usage Services Working Group (RUS-WG) [64] working group seeks to de ne resource usage as Grid services, the Grid Resource Allocation Agreement Protocol Working Group (GRAAP-WG) [65] seeks to address the protocol between a Super-Scheduler (Grid Level Scheduler) and local schedulers necessary to reserve and allocate resources in the Grid as a building block for this service Apart from OGSA, we have also studied WSRF, which is emerging as a promising standard for modelling stateful resources with Web services WSRF is replacing OGSI and is converging the efforts.

where E, is the dielectric constant of the semiconductor, the subscript p in the electron density (np) and hole density 'pp) refers to the respective quantity in a p-type semiconductor, Na is the ionized acceptor-dopant density, and ND+ is the ionized donor-dopant density.

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Optical Character Recognition on Android - OCR - Truiton
6 Nov 2016 ... Introducing an Android OCR Library – Text Recognition API ... keep things simple and scan the text from an image only, as this tutorial is targeted for beginners. ... Also the link to full source code is at the end of this tutorial.

Then, if there are [rn/21 bad observations on a particular corner, any regression estimate will break down; the breakdown point thus is, at best, [rn/21 /(md) 1/(2d) This value is reached by the &-estimate (which calculates the median at each corner) The conclusion is that the theories about high breakdown point regression are not really concerned with regression estimation, but with regression design-a proper choice of the latter is a prerequisite for obtaining good breakdown properties The theories show that high breakdown point regression estimates are possible for random designs, but not for optimal designs So the latter are not optimal if robustness is a concern This discussion will be continued in Section 1123 See also 9 for a different weakness of optimal designs At least in my experience, random carriers in regression are an exception rather than the rule.

As coding is completed and test execution is begun, software defects are discovered and tracked to correction. The relatively small size of the DCPS allows the developers to correct defects usually within 36 hours of detection and logging. With

That is, it would be a mistake to focus attention through tunnel vision on just one (tacit) goal, namely to safeguard at any cost against problems caused by gross errors in a random carrier Instead, more relevant issues to address would have been: (1) for a given (finite) design matrix X , find the best possible regression breakdown point, (2) investigate estimators approximating that breakdown point, and in particular, (3) find estimators achieving a good compromise between breakdown properties and efficiency Given all this, one should (4) construct better compromise designs that combine good efficiency and robustness properties As of now, neither the statistical nor the computational properties of high breakdown point regression estimators are adequately understood In my opinion, it would be a mistake to use any of them as a default regression estimator.

If very high contamination or mixture models are an issue, a straight data analytic approach through.

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Oct 24, 2018 · Comparing on-device text recognition tools on Android smartphones.

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