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Like you I also faced many problems implementing OCR in Android, but after much Googling I found the solution, and it surely is the best ...

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Optimality Criterion The eld speci es the optimality criterion for the scheduling problem and there are no sub elds All scheduling problems discussed in this book are about nding the shortest schedule length sl, which is represented by the symbol Cmax in the eld Here Ci stands for the completion time of task ni ; that is, Ci = tf (ni ), with Cmax = maxni V Ci being the maximum completion time of all tasks, which is the de nition of the schedule length (De nition 410) Examples The following examples illustrate the utilization of the | | notation A short | | notation without any optional eld, P||Cmax , refers to the problem of scheduling independent tasks with arbitrary computation costs on |P| identical processors such that the schedule length is minimized P2|prec, pi = 1|Cmax is the



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java - ocr - api -15.3.0.3.pom
4.0.0 com.asprise.ocr java - ocr - api 15.3.0.3 jar ${project.groupId}:${project. artifactId} A Java OCR SDK Library API allows you to perform OCR and bar code  ...

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There was no measurable performance gain in this case because this line of code was not a bottleneck and because all mobile phone CPUs have hardware multipliers.

Cell-Loss Probabilitiesa E1 ; E2 ; E3 1:5 10 2 ; 2 10 2 ; 10 2 2 10 3 ; 3 10 3 ; 1 10 3 10 2 ; 10 3 ; 1 10 4

E1 ; E2 , and E3 represent the cell-loss probabilities for Terminator, Gold nger, and Soccer, respectively.





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Asprise/java-.net-ocr-api-library: Asprise OCR SDK for Java ... - GitHub
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High performance, royalty-free Java OCR and barcode recognition on Windows, Linux, Mac OS and Unix. ... We offer hassle-free download of Asprise OCR Java trial kit to help you evaluate the OCR engine easily. You need to accept the terms and conditions set in LICENSE AGREEMENT FOR THE ...

these experiments. Note that without framing and active cell-discard, developing a solution for heterogeneous E1 ; E2 ; E3 is nontrivial. Effectiveness of the Firewall fCi g and Dropping Policy The effectiveness of guaranteeing a minimum capacity Ci per frame for class i and the dropping policy is evaluated next to the context of heterogeneous E values. This is achieved through trace-driven simulation. The scenario was as follows. MPEG-I video traces shown in Table 19.3 were used as input to the simulations. Their Ci were calculated using Alternative 2. The dispatcher was either the pseudo-earliest-due-date dispatcher described in Section 19.2.3 or LIFO for comparison purposes. In the experiments, each class had one connection. Also, the traces were phaseshifted randomly to ensure that they were mutually unsynchronized otherwise, one would have to consider correlated streams. Recall from Section 19.2.3, that when channel_image[] was full, the cell dispatcher gave preference to classes fjg that had not yet received at least Cj cell allocations in the current frame, and among those that did receive Cj , to those with smaller current estimates of the ratio Sj . The performance of the algorithm is shown in Table 19.3. Results for a simple last-in- rst-out (LIFO) dropping policy is also shown for comparison purposes. In

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Tess4J - Tesseract for Java - javalibs
Tess4J ## Description: A Java JNA wrapper for Tesseract OCR API. Tess4J is released and distributed under the Apache License, v2.0. ## Features: The library ...

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TABLE 19.3 Performance of the Proposed Cell Dispatcher for Heterogeneous Cell-Loss Probabilities, fEi g Experiment Number I II Video Trace Terminator Gold nger Soccer Terminator Gold nger Soccer Ei Desired 0.01 0.001 0.0001 0.002 0.003 0.001 Ei Delivered (LIFO) 0.0008 0.0012 0.0011 0.0014 0.0020 0.0018 Ei Delivered (Proposed Dispatcher) 0.0039 0.00096 0.00009 0.0019 0.0029 0.0007

LIFO, newly active nonguaranteed cells that found the channel_image full were dropped. The results show a need for the priority scheduler. 19.4.2 Equivalent Bandwidth for Heterogeneous Frames

Let there be L delay-jitter classes, each with a different delay-jitter bound and corresponding frame size. Let nl l 1; . . . ; L be the number of connections belonging to class l. For class l in isolation, the aggregate capacity needed to meet prescribed cell-loss probabilities may be computed in accordance with Section 19.4.1. Let Cl be the capacity needed for class l traf c. Then an upper bound on P capacity needed for all classes is l Cl . 19.4.3 Loss-Free Transmission

In Section 7.4, we stated that one of the most important rules for optimization was getting the design right. For instance, it should be possible to defer the choice of sorting algorithm until the trade-offs between bubble sort, quick sort, or some other algorithm can be made intelligently on the basis of performance, memory requirements and the size and distribution of the data set to be sorted. However, this requires designing your code such that substituting one sorting algorithm for another is painless. This section looks at a couple of patterns that can help achieve a better design.

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Tesseract: Simple Java Optical Character Recognition - Stack Abuse
12 Aug 2019 ... For these tasks, Optical Character Recognition ( OCR ) was devised as a way to allow computers to "read" graphical content as text , similar to ...

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