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Asprise Java OCR (optical character recognition) and barcode recognition SDK offers a high performance API library for you to equip your Java applications ... 66 CONCLUDING REMARKS This chapter studied advanced aspects of task scheduling The rst sections presented scheduling techniques that are utilized in scheduling algorithms to improve the quality of the produced schedules The insertion technique tries to use idle slots between already scheduled nodes to improve the processor utilization ef ciency Node duplication, on the other hand, aims at reducing the communication costs of schedules Following the framework approach of this text, they were analyzed detached from concrete algorithms in a general manner Up to that point, everything was based on the scheduling model as introduced in Section 41 In Section 63 it was extended toward heterogeneous processors The extension is simple but powerful nd most of the discussed scheduling techniques can be employed with little or no modi cation After this, the chapter returned to a topic that had been more or less skipped in 4 the analysis of special cases of the scheduling problem Unfortunately, most of them remain NP-hard, as could be seen in the extensive survey of scheduling problems in Section 64 The survey employed the | | notation for the classi cation of the various scheduling problems As the scheduling problem is in general NP-hard, genetic algorithms have been employed for its solution This chapter discussed how genetic algorithms can be applied to task scheduling and the implications of different approaches Genetic algorithms are employed in many other areas apart from task scheduling But the GA approach is not the only generic technique that has been applied to task scheduling Integer linear programming (ILP) is a technique that is utilized for all sorts of scheduling problems Hanen and Munier [85] formulate an integer linear programming (ILP) based algorithm for task scheduling Another universal technique, which has been applied recently to task scheduling (Kwok and Ahmad [115]) is A* search (Berman and Paul [22]) In contrast to stochastic search algorithms,A* explores the entire search space systematically and therefore obtains the optimal result It tries to reduce the runtime by pruning of unpromising state subtrees For task scheduling, its runtime is nevertheless exponential; therefore, it can only be applied to relatively small graphs It goes without saying that there are many other interesting aspects of scheduling One last example shall be scheduling tools Many task scheduling algorithms have been implemented in graph based parallelization tools In the parallelization process of such tools, a graph is generated from an initial program speci cation This. java ocr core example: Tess4J - JNA wrapper for Tesseract java-ocr-api maven Cloud Vision API Client Library for Java | Google Developers
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Aspose. OCR for Java is a stand-alone OCR API for Java applications while allowing the developers to perform optical character recognition on commonly used ... ocr library java maven Tess4J - JNA wrapper for Tesseract
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