Image segmentation is a fundamental problem in biomedical image analysis. Recent advances in deep learning have achieved promising results on many biomedical image segmentation benchmarks. However, due to large variations in biomedical images (different modalities, image settings, objects, noise, etc), to utilize deep learning on a new application, it usually needs a new set of training data. T...

We show that the 0 2 enumeration degrees are not dense. This answers a question posed by Cooper. 1 Background Cooper 3] showed that the enumeration degrees (e-degrees) are not dense. He also showed that the e-degrees of the 0 2 sets are dense 2]. Since Cooper's nondensity proof constructs a 0 7 set, he posed the question: What is the least n (2 n 6) such that the e-degrees below 0 n are not den...

Test set compaction is a fundamental problem in digital system testing. In recent years, many competitive solutions have been proposed, most of which based on heuristics approaches. This paper studies the application of set covering models to the compaction of test sets, which can be used with any heuristic test set compaction procedure. For this purpose, recent and highly effective set coverin...

We study reductions that limit the extreme adaptivity of Turing reductions. In particular, we study reductions that make a rapid, structured progression through the set to which they are reducing: Each query is strictly longer (shorter) than the previous one. We call these reductions query-increasing (query-decreasing) Turing reductions. We also study query-nonincreasing (querynondecreasing) Tu...

The paper is concerned with the problem of binary classification of data records, given an already classified training set of records. Among the various approaches to the problem, the methodology of the logical analysis of data (LAD) is considered. Such approach is based on discrete mathematics, with special emphasis on Boolean functions. With respect to the standard LAD procedure, enhancements...

We examine the set covering machine when it uses data-dependent half-spaces for its set of features and bound its generalization error in terms of the number of training errors and the number of half-spaces it achieves on the training data. We show that it provides a favorable alternative to data-dependent balls on some natural data sets. Compared to the support vector machine, the set covering...

Geopersia is published biannually by the College of Science, University of Tehran, Iran. The College of Science published Journal of Science, which covered all fields of basic science, from 1968 to 2010. It was then decided that the College’s journals should be more specialized, and hence publication of Geopersia was launched. Articles printed in Geopersia will be available online too. Aims an...

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The original q-Markov Covariance Equivalent Realization (q-Markov Cover) method for identification required white noise test signals, which can not be generated exactly. This paper replaces the unrealizable white noise signal with a realizable signal (the Pseudo Random Binary Signal (PRBS)), and proves that when the period of the PRBS approaches infinity the q-Markov Cover algorithm, operating ...