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Tesseract : Simple Java Optical Character Recognition - Stack Abuse
12 Aug 2019 ... It offers an API for a bunch of languages, though we'll focus on the Tesseract Java API . Tesseract is very easy to implement, and subsequently ...

compensation e is scheduled on P3 (vice versa in the classic model (Figure 51)) Also, f is scheduled on P1 to avoid contention on L1 Figure 720(a) shows the intermediate schedule at this point Then, g and i are scheduled on the processors of their parent nodes The following node h is decisive for the rest of the schedule: its earliest start time is on P1 , but its entering edge eeh now blocks L1 for the entering communication of j, which is quite large Thus, j and k must be scheduled on P1 The nal schedule length (24) (Figure 720(b)) is not longer than in the classic model (Figure 51), but here more nodes are executed on P1 and less interprocessor communications are performed Hence, list scheduling achieves in this example the desired contention awareness in its scheduling decisions In general, the schedule lengths under the contention model and the classic model are not directly comparable Contention aware scheduling produces normally longer schedules, but shorter execution times on real machines The experiments in Sinnen and Sousa [172, 176] verify this Complexity The complexity of contention aware list scheduling is similar to list scheduling under the classic model (Section 51) Essentially, only the calculation of the DRT is more complex than in the classic model For example, the complexity of the second part of simple list scheduling (Algorithm 9) with start time minimization and the end technique is as follows To calculate the start time of a node n, the data ready time tdr (n) is computed, which involves the scheduling of n s entering edges The scheduling of an edge includes the determination of the route and its scheduling on each link of the route This is described by O(routing) (see Section 722) for each edge If the route can be determined in O(1) time (calculated or looked up), then O(routing) is just the complexity of the length of the route, as the edge must be scheduled on each link of the route So for all nodes on all processors, calculating the DRT amortizes to O(PEO(routing)) The start time of every node is computed on every processor, that is, O(PV) times; hence, the total complexity is O(P(V + EO(routing))) In comparison, the complexity under the classic model is O(P(V + E)) and with the insertion technique O(V2 + PE) (Section 61) Using the insertion technique in contention aware list scheduling has a complexity of O(V2 + PE2 O(routing)), as the calculation of an edge s start time changes from O(1) to O(E), since there are at most O(E) edges on each link As discussed in Section 722, for any systems O(routing) is at most linear in the number of processors |P| and links |L| Sorting the entering edges of each node according to some heuristic amortizes to O(E log E) for all nodes Thus, the complexity of the second part of list scheduling is then O(P(V + EO(routing)) + E log E) using the end technique and remains O(V2 + PE2 O(routing)) using the insertion technique.



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Asprise Java OCR library offers a royalty-free API that converts images (in formats like JPEG, PNG, TIFF, PDF, etc.) into editable document formats Word, XML, ...

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Hi guys, so I have been given a project to do that uses OCR to read some text from images. I've never used an OCR library so this is something very new to me.

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Java JNA wrapper for Tesseract OCR API. Contribute to nguyenq/tess4j development by creating an account on GitHub .

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In many ways, you can think of AIR itself as a library of code designed to provide a simple interface for evelopers working with complex systems For each operating system, there are different APIs for storing files, getting data from the clipboard, or finding information such as the user s screen dimensions Developers will occasionally decide not to use an existing library because they feel that they could create a more efficient solution themselves This is often realistic: Open-source libraries are often designed to fit a wide array of uses, while a specific application is likely to only need a subset of those uses This means that there is code in the library that you don t need for your project; you could write a library to perform a similar task without the added overhead.

For example, the Papervision 3D library contains a robust camera object, which allows developers to change the perspective on the scene they are viewing or to programmatically move through a scene If you are creating an application that requires 3D, but does not need to have a dynamic camera, then it might be reasonable to expect that you could create a new 3D engine without a camera, and that your engine might be more efficient as a result However, it is obviously not a small task to develop a 3D engine, so you would need to develop and test your new library If you were to leverage an open-source library, you could generally depend on the code you use to be tested and relatively stable.

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Using Barcode generation for Visual Studio .NET Control to generate create PDF417 image in .NET framework applications. Also in most cases the library compound is leaved from the resin before encoding so that overlap of the 19F signal does not become an issue. A recent report20 uses a uorine encoding method for the rst position monomers in a mix and split library to assist in the mass spectral deconvolution of library hits. Mass spectroscopy is used as the primary structural deconvolution tool. However, due to mass redundancies in the screened pools, mass spectral analysis alone cannot unequivocally determine the structure of the hits. Thus, to avoid having to re-synthesize numerous compounds, 19F encoding is used to provide additional structural information. A hybrid structural determination strategy is employed that relies on mass spectral analysis of the active bead coupled with on-bead analysis of the rst position nonreleasable code. This strategy reduces the number of structural possibilities to a single structure in every case. In practice, a series of commercially available uorine carboxylic acids are used to generate an encoding system for mix and split libraries. The tags are attached to the resin via an amide bond, and each tag displays a unique distinguishable uorine chemical shift. A large number of codes may be generated from a small set of differentiable uorine carboxylic acid tags. Combinations of two uorine tags are used at a time, along with 50 to 100 rst-position encoded resin pools that require 11 to 15 individual tags. The large batches of encoded resin are synthesized as outlined in Scheme 2.12.Related: QR Code Generator .NET , QR Code Generation .NET Image, .NET QR Code Generation Size

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optical-character-recognition · GitHub Topics · GitHub
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