Relevant bibliographies by topics / Counting-set automata

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  1. Journal articles
  2. Dissertations / Theses
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  4. Conference papers

Academic literature on the topic 'Counting-set automata'

Author: Grafiati
Published: 28 June 2021
Last updated: 17 February 2022

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Journal articles on the topic "Counting-set automata"

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Turoňová, Lenka, Lukáš Holík, Ondřej Lengál, Olli Saarikivi, Margus Veanes, and Tomáš Vojnar. "Regex matching with counting-set automata." Proceedings of the ACM on Programming Languages 4, OOPSLA (November 13, 2020): 1–30. http://dx.doi.org/10.1145/3428286.

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SCHEICHER, KLAUS, and JÖRG M. THUSWALDNER. "Canonical number systems, counting automata and fractals." Mathematical Proceedings of the Cambridge Philosophical Society 133, no. 1 (July 2002): 163–82. http://dx.doi.org/10.1017/s0305004102005856.

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In this paper we study properties of the fundamental domain [Fscr ]β of number systems, which are defined in rings of integers of number fields. First we construct addition automata for these number systems. Since [Fscr ]β defines a tiling of the n-dimensional vector space, we ask, which tiles of this tiling ‘touch’ [Fscr ]β. It turns out that the set of these tiles can be described with help of an automaton, which can be constructed via an easy algorithm which starts with the above-mentioned addition automaton. The addition automaton is also useful in order to determine the box counting dimension of the boundary of [Fscr ]β. Since this boundary is a so-called graph-directed self-affine set, it is not possible to apply the general theory for the calculation of the box counting dimension of self similar sets. Thus we have to use direct methods.
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HOLZER, MARKUS, and SEBASTIAN JAKOBI. "FROM EQUIVALENCE TO ALMOST-EQUIVALENCE, AND BEYOND: MINIMIZING AUTOMATA WITH ERRORS." International Journal of Foundations of Computer Science 24, no. 07 (November 2013): 1083–97. http://dx.doi.org/10.1142/s0129054113400327.

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We introduce E-equivalence, which is a straightforward generalization of almost-equivalence. While almost-equivalence asks for ordinary equivalence up to a finite number of exceptions, in E-equivalence these exceptions or errors must belong to a (regular) set E. The computational complexity of deterministic finite automata (DFAs) minimization problems and their variants w.r.t. almost- and E-equivalence are studied. We show that there is a significant difference in the complexity of problems related to almost-equivalence, and those related to E-equivalence. Moreover, since hyper-minimal and E-minimal automata are not necessarily unique (up to isomorphism as for minimal DFAs), we consider the problem of counting the number of these minimal automata.
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Marchant, Ross, Martin Tetard, Adnya Pratiwi, Michael Adebayo, and Thibault de Garidel-Thoron. "Automated analysis of foraminifera fossil records by image classification using a convolutional neural network." Journal of Micropalaeontology 39, no. 2 (October 15, 2020): 183–202. http://dx.doi.org/10.5194/jm-39-183-2020.

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Abstract. Manual identification of foraminiferal morphospecies or morphotypes under stereo microscopes is time consuming for micropalaeontologists and not possible for nonspecialists. Therefore, a long-term goal has been to automate this process to improve its efficiency and repeatability. Recent advances in computation hardware have seen deep convolutional neural networks emerge as the state-of-the-art technique for image-based automated classification. Here, we describe a method for classifying large foraminifera image sets using convolutional neural networks. Construction of the classifier is demonstrated on the publicly available Endless Forams image set with a best accuracy of approximately 90 %. A complete automatic analysis is performed for benthic species dated to the last deglacial period for a sediment core from the north-eastern Pacific and for planktonic species dated from the present until 180 000 years ago in a core from the western Pacific warm pool. The relative abundances from automatic counting based on more than 500 000 images compare favourably with manual counting, showing the same signal dynamics. Our workflow opens the way to automated palaeoceanographic reconstruction based on computer image analysis and is freely available for use.
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Ying, Yu Ming, and Xiao Hong Yang. "Automatic Counting System Based on MCU." Applied Mechanics and Materials 273 (January 2013): 547–50. http://dx.doi.org/10.4028/www.scientific.net/amm.273.547.

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For the low accuracy and low efficiency of artificial counting problem, we introduced a set of automatic counting system which can be applied in the particulate workpiece counting. With infrared transmitting and receiving module as sensor, when a workpiece passes through the surveyed area, the light will be blocked by the workpiece and the receiving module will emit a pulse signal, the counting for the passing workpiece just is the workpiece number. This text make detailed introduction to the hardware circuit and software design and An on-line type automatic control photoelectric counter system is developed based on this photoelectric detection method. The experiments show that the instrument has the advantages of precision counting, fast detection speed and strong practicability.
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Fernandez-Gallego, Jose, Ma Buchaillot, Nieves Aparicio Gutiérrez, María Nieto-Taladriz, José Araus, and Shawn Kefauver. "Automatic Wheat Ear Counting Using Thermal Imagery." Remote Sensing 11, no. 7 (March 28, 2019): 751. http://dx.doi.org/10.3390/rs11070751.

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Ear density is one of the most important agronomical yield components in wheat. Ear counting is time-consuming and tedious as it is most often conducted manually in field conditions. Moreover, different sampling techniques are often used resulting in a lack of standard protocol, which may eventually affect inter-comparability of results. Thermal sensors capture crop canopy features with more contrast than RGB sensors for image segmentation and classification tasks. An automatic thermal ear counting system is proposed to count the number of ears using zenithal/nadir thermal images acquired from a moderately high resolution handheld thermal camera. Three experimental sites under different growing conditions in Spain were used on a set of 24 varieties of durum wheat for this study. The automatic pipeline system developed uses contrast enhancement and filter techniques to segment image regions detected as ears. The approach is based on the temperature differential between the ears and the rest of the canopy, given that ears usually have higher temperatures due to their lower transpiration rates. Thermal images were acquired, together with RGB images and in situ (i.e., directly in the plot) visual ear counting from the same plot segment for validation purposes. The relationship between the thermal counting values and the in situ visual counting was fairly weak (R2 = 0.40), which highlights the difficulties in estimating ear density from one single image-perspective. However, the results show that the automatic thermal ear counting system performed quite well in counting the ears that do appear in the thermal images, exhibiting high correlations with the manual image-based counts from both thermal and RGB images in the sub-plot validation ring (R2 = 0.75–0.84). Automatic ear counting also exhibited high correlation with the manual counting from thermal images when considering the complete image (R2 = 0.80). The results also show a high correlation between the thermal and the RGB manual counting using the validation ring (R2 = 0.83). Methodological requirements and potential limitations of the technique are discussed.
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Gallardo-Caballero, Ramón, Carlos J. García-Orellana, Antonio García-Manso, Horacio M. González-Velasco, Rafael Tormo-Molina, and Miguel Macías-Macías. "Precise Pollen Grain Detection in Bright Field Microscopy Using Deep Learning Techniques." Sensors 19, no. 16 (August 17, 2019): 3583. http://dx.doi.org/10.3390/s19163583.

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The determination of daily concentrations of atmospheric pollen is important in the medical and biological fields. Obtaining pollen concentrations is a complex and time-consuming task for specialized personnel. The automatic location of pollen grains is a handicap due to the high complexity of the images to be processed, with polymorphic and clumped pollen grains, dust, or debris. The purpose of this study is to analyze the feasibility of implementing a reliable pollen grain detection system based on a convolutional neural network architecture, which will be used later as a critical part of an automated pollen concentration estimation system. We used a training set of 251 videos to train our system. As the videos record the process of focusing the samples, this system makes use of the 3D information presented by several focal planes. Besides, a separate set of 135 videos (containing 1234 pollen grains of 11 pollen types) was used to evaluate detection performance. The results are promising in detection (98.54% of recall and 99.75% of precision) and location accuracy (0.89 IoU as the average value). These results suggest that this technique can provide a reliable basis for the development of an automated pollen counting system.
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Becker, D. E. "Algorithms for automated montage synthesis of images from laser-scanning confocal microscopes." Proceedings, annual meeting, Electron Microscopy Society of America 53 (August 13, 1995): 650–51. http://dx.doi.org/10.1017/s0424820100139627.

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An efficient, robust, and widely-applicable technique is presented for computational synthesis of high-resolution, wide-area images of a specimen from a series of overlapping partial views. This technique can also be used to combine the results of various forms of image analysis, such as segmentation, automated cell counting, deblurring, and neuron tracing, to generate representations that are equivalent to processing the large wide-area image, rather than the individual partial views. This can be a first step towards quantitation of the higher-level tissue architecture. The computational approach overcomes mechanical limitations, such as hysterisis and backlash, of microscope stages. It also automates a procedure that is currently done manually. One application is the high-resolution visualization and/or quantitation of large batches of specimens that are much wider than the field of view of the microscope.The automated montage synthesis begins by computing a concise set of landmark points for each partial view. The type of landmarks used can vary greatly depending on the images of interest. In many cases, image analysis performed on each data set can provide useful landmarks. Even when no such “natural” landmarks are available, image processing can often provide useful landmarks.
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Marin, Ambroise, Emmanuel Denimal, Stéphane Guyot, Ludovic Journaux, and Paul Molin. "A Robust Generic Method for Grid Detection in White Light Microscopy Malassez Blade Images in the Context of Cell Counting." Microscopy and Microanalysis 21, no. 1 (December 16, 2014): 239–48. http://dx.doi.org/10.1017/s1431927614013671.

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AbstractIn biology, cell counting is a primary measurement and it is usually performed manually using hemocytometers such as Malassez blades. This work is tedious and can be automated using image processing. An algorithm based on Fourier transform filtering and the Hough transform was developed for Malassez blade grid extraction. This facilitates cell segmentation and counting within the grid. For the present work, a set of 137 images with high variability was processed. Grids were accurately detected in 98% of these images.
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Kuske, Dietrich, and Markus Lohrey. "First-order and counting theories of ω-automatic structures." Journal of Symbolic Logic 73, no. 1 (March 2008): 129–50. http://dx.doi.org/10.2178/jsl/1208358745.

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AbstractThe logic extends first-order logic by a generalized form of counting quantifiers (“the number of elements satisfying … belongs to the set C”). This logic is investigated for structures with an injectively ω-automatic presentation. If first-order logic is extended by an infinity-quantifier, the resulting theory of any such structure is known to be decidable [6]. It is shown that, as in the case of automatic structures [21], also modulo-counting quantifiers as well as infinite cardinality quantifiers (“there are many elements satisfying …”) lead to decidable theories. For a structure of bounded degree with injective ω-automatic presentation, the fragment of that contains only effective quantifiers is shown to be decidable and an elementary algorithm for this decision is presented. Both assumptions (ω-automaticity and bounded degree) are necessary for this result to hold.
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Dissertations / Theses on the topic "Counting-set automata"

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Horký, Michal. "Rychlejší než grep pomocí čítačů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445473.

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Vyhledávání regulárních výrazů má ve vývoji softwaru nezastupitelné místo. Rychlost vyhledávání může ovlivnit použitelnost softwaru, a proto je na ni kladen velký důraz. Pro určité druhy regulárních výrazů mají standardní přístupy pro vyhledávání vysokou složitost. Kvůli tomu jsou náchylné k útokům založeným na vysoké náročnosti vyhledávání regulárních výrazů (takzvané ReDoS útoky). Regulární výrazy s omezeným opakováním, které se v praxi často vyskytují, jsou jedním z těchto druhů. Efektivní reprezentace a rychlé vyhledávání těchto regulárních výrazů je možné s použítím automatu s čítači. V této práci představujeme implementaci vyhledávání regulárních výrazů založeném na automatech s čítači v C++. Vyhledávání je implementováno v rámci RE2, rychlé moderní knihovny pro vyhledávání regulárních výrazů. V práci jsme provedli experimenty na v praxi používaných regulárních výrazech. Výsledky experimentů ukázaly, že implementace v rámci nástroje RE2 je rychleší než původní implementace v jazyce C#.
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Book chapters on the topic "Counting-set automata"

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Pan, Minghua, Hengbing Wei, and Shaohua Sun. "Application of Typical Set on Automatic Counting of Round Brilliant Cut Gems." In Communications in Computer and Information Science, 17–26. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2260-9_3.

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Chen, Yangjun. "A New Algorithm for Subset Matching Problem Based on Set-String Transformation." In Encyclopedia of Information Communication Technology, 607–15. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-59904-845-1.ch080.

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In computer engineering, a number of programming tasks involve a special problem, the so-called tree matching problem (Cole & Hariharan, 1997), as a crucial step, such as the design of interpreters for nonprocedural programming languages, automatic implementation of abstract data types, code optimization in compilers, symbolic computation, context searching in structure editors and automatic theorem proving. Recently, it has been shown that this problem can be transformed in linear time to another problem, the so called subset matching problem (Cole & Hariharan, 2002, 2003), which is to find all occurrences of a pattern string p of length m in a text string t of length n, where each pattern and text position is a set of characters drawn from some alphabet S. The pattern is said to occur at text position i if the set p[j] is a subset of the set t[i + j - 1], for all j (1 = j = m). This is a generalization of the ordinary string matching and is of interest since an efficient algorithm for this problem implies an efficient solution to the tree matching problem. In addition, as shown in (Indyk, 1997), this problem can also be used to solve general string matching and counting matching (Muthukrishan, 1997; Muthukrishan & Palem, 1994), and enables us to design efficient algorithms for several geometric pattern matching problems. In this article, we propose a new algorithm on this issue, which needs only O(n + m) time in the case that the size of S is small and O(n + m·n0.5) time on average in general cases.
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Turing, Alan. "Lecture on the Automatic Computing Engine (1947)." In The Essential Turing. Oxford University Press, 2004. http://dx.doi.org/10.1093/oso/9780198250791.003.0015.

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On 8 December 1943 the world’s first large-scale special-purpose electronic digital computer—‘Colossus’, as it became known—went into operation at the Government Code and Cypher School (see ‘Computable Numbers: A Guide’, ‘Enigma’, and the introduction to Chapter 4). Colossus was built by Thomas H. Flowers and his team of engineers at the Post Office Research Station in Doll is Hill, London. Until relatively recently, few had any idea that electronic digital computation was used successfully during the Second World War, since those who built and worked with Colossus were prohibited by the Official Secrets Act from sharing their knowledge. Colossus contained approximately the same number of electronic valves (vacuum tubes) as von Neumann’s IAS computer, built at the Princeton Institute of Advanced Study and dedicated in 1952. The IAS computer was forerunner of the IBM 701, the company’s first mass-produced stored-programme electronic computer (1953). The first Colossus had 1,600 electronic valves and Colossus II, installed in mid-1944, 2,400, while the IAS computer had 2,600. Colossus lacked two important features of modern computers. First, it had no internally stored programmes (see ‘Computable Numbers: A Guide’). To set up Colossus for a new task, the operators had to alter the machine’s physical wiring, using plugs and switches. Second, Colossus was not a general-purpose machine, being designed for a specific cryptanalytic task (involving only logical operations and counting). Nevertheless, Flowers had established decisively and for the first time that large-scale electronic computing machinery was practicable. The implication of Flowers’s racks of electronic equipment would have been obvious to Turing. Once Turing had seen Colossus it was, Flowers said, just a matter of Turing’s waiting to see what opportunity might arise to put the idea of his universal computing machine into practice. Precisely such an opportunity fell into Turing’s lap in 1945, when John Womersley invited him to join the Mathematics Division of the National Physical Laboratory (NPL) at Teddington in London, in order to design and develop an electronic stored-programme digital computer—a concrete form of the universal Turing machine of 1936.
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Conference papers on the topic "Counting-set automata"

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Khan, Sana Ullah, Naveed Islam, Zahoor Jan, Hameed Ullah Shah, and Aziz ud Din. "Automated Counting of Cells in Breast Cytology Images Using Level Set Method." In 2018 IEEE 20th International Conference on High Performance Computing and Communications; IEEE 16th International Conference on Smart City; IEEE 4th International Conference on Data Science and Systems (HPCC/SmartCity/DSS). IEEE, 2018. http://dx.doi.org/10.1109/hpcc/smartcity/dss.2018.00258.

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