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Oct 14, 2019 · Free, open source and cross-platform. Tesseract is licensed under the Apache with source code available on GitHub. It's available for free on ...

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Tess4J download | SourceForge.net
A Java JNA wrapper for Tesseract OCR API. ... Java OCR is a suite of pure java libraries for image processing and character... ... Provides optical character recognition ( OCR ) solutions for Vietnamese language.

The average entropy remains a function of T1 ; T2 : that is, S S T1 ; T2 . Figure 18.4 plots S T1 ; T2 S T1 (recall that T1 T2 ) for the a 1:05 throughput series as a function of time scale or aggregation level T1 . Entropy is highest for small time scales in the range $250 ms, and it drops monotonically as T1 is increased. Eventually, S T1 begins to atten out near the 3 5 second mark, reaching saturation, and stays so as time scale is further increased. From our analysis of various long-range dependent traf c traces, we nd that the ``knee'' of the entropy curve is in the range of 1 5 seconds. Note that increasing T1 further and further to gain small decreases in entropy brings forth with it an important problem, namely, if prediction is done over a ``too long'' time interval, then the information may not be effectively exploitable by various congestion control strategies. In the next section,



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Development with Tess4J in NetBeans, Eclipse, and Command-line
Add a new Java Class file named TesseractExample with appropriate ... In project's Properties window, select Java Build Path > Add External JARs... and add ...

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TextApp. java example - Javatips.net
This class describes the usage of TextApp. java . ... JacksonFactory; import com. google . api .services. vision .v1. Vision ; import com. google . api .services. vision .v1.

The previous chapter introduced the two fundamental scheduling algorithms: list scheduling and clustering In this chapter, the focus is on more advanced aspects of task scheduling The rst sections are dedicated to general techniques, which are not scheduling algorithms as such but are techniques that are used in combination with the fundamental algorithms Following the framework approach utilized so far, they are studied detached from concrete algorithms in a general manner The insertion technique (Section 61) is a generalization of the end technique (De nition 52), where nodes no longer need to be scheduled after already scheduled nodes With node duplication (Section 62), one node might be executed on more than one processor The goal is to save communication costs, as node duplication can make more communications local The classic target system model (De nition 43) used so far assumes that all processors are identical regarding their processing speed In real parallel systems, this is not always given Section 63 extends the scheduling model toward heterogeneous processors This is done in a simple but powerful way, which leaves almost all scheduling concepts studied so far unaffected Section 64 returns to the more theoretical side of task scheduling It studies the NP-hardness of many variations of the scheduling problem introduced in 4 A completely different approach to scheduling, based on genetic algorithms, is analyzed in Section 65 A genetic algorithm is a stochastic search based on the principles of evolution The concluding remarks of this chapter will provide some references to further task scheduling publications





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Asprise Java OCR SDK - royalty-free API library with source code ...
Asprise Java OCR library offers a royalty-free API that converts images (in ... Download a copy of Asprise OCR SDK from ... Put aocr. jar into your class path ...

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Java Code Examples net.sourceforge.tess4j.Tesseract
This page provides Java code examples for net.sourceforge.tess4j. ... Project: hadoop-video- ocr File: HadoopOCR . java View source code, 10 votes, vote down  ...

Aggregation Level (seconds)

we show that one strategy selective aggressiveness is effective at exploiting the predictability structure found in the 1 5 second range.

Running the loop increased battery consumption from 66 mA to an unacceptable 163mA on my Psion Series 5MX (unfortunately there is no easy way of monitoring battery consumption on more recent mobile phones). The battery consumption returned to 66 mA when keepRunning was set to false. Further, loops like this will hog the CPU and deprive other applications of CPU cycles. In order to read from an InputStream we can sit in a loop polling for the number of available bytes using InputSteam.available(). When data becomes available, we read it using InputStream.read(). However, it is far better to create a separate reader thread that calls InputStream.read() directly. Because this method blocks, the thread will wait until data is present and not consume any unnecessary CPU bandwidth. Although both an event model and a wait notify model require an extra Thread, this is generally worthwhile.

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Comparison of optical character recognition software - Wikipedia
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In this section we present a congestion control strategy called selective aggressiveness control (SAC) and show its ef cacy at exploiting the predictability structure present in long-range dependent traf c for improving network performance. Our control scheme is a form of predictive congestion control based on the multiple time scale congestion control framework (MTSC) [46]. Explicit prediction of the long term network state l is performed at SAC's time scale (1 5 seconds). A certain control action e l is made by SAC based on this information about the future and is incorporated into the underlying congestion control to affect traf c control decisions. The overall structure is shown in Figure 18.5. SAC is aimed to be robust, ef cient, and portable such that it can easily be incorporated into existing congestion control schemes. SAC's modus operandi is to complement and help improve the performance of existing reactive congestion controls. Toward this end, we set up a simple, generic rate-based feedback congestion control as a reference and let our control module ``run on top'' of it. SAC always respects the decision made by the underlying congestion control with respect to the directional change of the traf c rate up or down; however, it may choose to adjust the magnitude of change. That is, if, at any time, the underlying congestion control decides to increase its sending rate, SAC will never take the opposite action and decrease the sending rate. Instead, what SAC

61 INSERTION TECHNIQUE In Section 51, the most common technique for the node s start time determination the end technique (De nition 52) was presented On a given processor P, a node is scheduled at the end of all nodes already scheduled on this processor

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Tess4J Tutorial with Maven And Java – Linux Hint
In this lesson on Tesseract with Java and Maven, we will see how we can develop ... Tess4J is simply described as a Java JNA wrapper for Tesseract OCR API .












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