Building of a recognition algorithms (RA) based on the selection of representative pseudo-objects and providing a solution to the problem of recognition of objects represented in a big-dimensionality feature space (BD...
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ISBN:
(纸本)9783030941413;9783030941406
Building of a recognition algorithms (RA) based on the selection of representative pseudo-objects and providing a solution to the problem of recognition of objects represented in a big-dimensionality feature space (BDFS) are described in this article. The proposed approach is based on the formation of a set of 2D basic pseudo-objects and the determination of a suitable set of 2D proximity functions (PF) when designing an extreme RA. The article contains a parametric description of the proposed RA. It is presented in the form of sequence of computational procedures. And the main ones are procedures for determining: the functions of differences among objects in a 2D subspace of representative features (TSRF);groups of interconnectedness pseudo-objects (GIPO) in the same subspace;a set of basic pseudo-objects;functions of differences between the basic pseudo-object in a TSRF. There are also groups of interconnectedness and basic PF;the integral recognizing operator with respect to basic PF. The results of a comparative analysis of the proposed and known RA are presented. The main conclusion is that the implementation of the approach proposed in this paper makes it possible to switch from the original BDFS to the space of representative features (RF), the dimension of which is significantly lower.
The human face is one of the most visible features of our unique identity as individuals. Interestingly, mono -zygotic twins share almost identical facial traits and the same DNA sequence but could exhibit differences...
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The human face is one of the most visible features of our unique identity as individuals. Interestingly, mono -zygotic twins share almost identical facial traits and the same DNA sequence but could exhibit differences in other biometrical parameters. The expansion of the world wide web and the possibility to exchange pictures of humans across the planet has increased the number of people identified online as virtual twins or doubles that are not family related. Herein, we have characterized in detail a set of "look-alike"humans, defined by facial recognition algorithms, for their multiomics landscape. We report that these individuals share similar genotypes and differ in their DNA methylation and microbiome landscape. These results not only provide in-sights about the genetics that determine our face but also might have implications for the establishment of other human anthropometric properties and even personality characteristics.
recognition algorithms determining whether a given matroid is binary signed-graphic or not are presented in this work. Depending on whether the input is a cographic, a binary or a general matroid different algorithms ...
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recognition algorithms determining whether a given matroid is binary signed-graphic or not are presented in this work. Depending on whether the input is a cographic, a binary or a general matroid different algorithms are provided utilizing mainly decomposition results for the class of signed-graphic matroids. Finally, in order to devise such algorithms, necessary results regarding the representability of signed-graphic matroids in various fields are also given. (C) 2020 Elsevier B.V. All rights reserved.
Several well-studied classes of graphs admit structural characterizations via proper 2-cutsets which lead to polynomial-time recognition algorithms. The algorithms so far obtained for those recognition problems do not...
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Several well-studied classes of graphs admit structural characterizations via proper 2-cutsets which lead to polynomial-time recognition algorithms. The algorithms so far obtained for those recognition problems do not guarantee linear-time complexity. The bottleneck to those algorithms is the Omega(nm)-time complexity to fully decompose by proper 2-cutsets a graph with n vertices and m edges. In the present work, we investigate the 3-connected components of a graph and propose the use of the SPQR-tree data structure to obtain a fully decomposed graph in linear time. As a consequence, we show that the recognition of chordless graphs and of graphs that do not contain a propeller as a subgraph can be done in linear time, answering questions in the existing literature. (C) 2017 Elsevier B.V. All rights reserved.
This paper provides a preliminary survey of the algoritms used in ISAR imaging for the ship recognition. It provides an overview of existing literature and summarises the current state on a topic. The author of the pa...
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ISBN:
(纸本)9781509025183
This paper provides a preliminary survey of the algoritms used in ISAR imaging for the ship recognition. It provides an overview of existing literature and summarises the current state on a topic. The author of the paper focuses on the algorithms for a single target.
The mathematical model of a digital radiation image is given that corresponds to a test object that contains two types of defects, namely, pores and cracks (or non-penetrating defects). Two algorithms for automatic im...
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The mathematical model of a digital radiation image is given that corresponds to a test object that contains two types of defects, namely, pores and cracks (or non-penetrating defects). Two algorithms for automatic image recognition of these defects on a digital radiation image of an object are given. The effectiveness of the algorithms was evaluated via mathematical simulation.
In this work we provide a decomposition theorem for a class of quaternary signed- graphic matroids. The decomposition is based on k- sums and a new operation called star composition, while the building blocks are grap...
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In this work we provide a decomposition theorem for a class of quaternary signed- graphic matroids. The decomposition is based on k- sums and a new operation called star composition, while the building blocks are graphic matroids and nongraphic matroids which become graphic upon the deletion of any co circuit. This result generalizes previous results for binary signed-graphic matroids and graphic matroids, and it provides the theoretical basis for a recognition algorithm.
Visual speech recognition is a technology that relies on visual information, offering unique advantages in noisy environments or when communicating with individuals with speech impairments. However, this technology st...
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Visual speech recognition is a technology that relies on visual information, offering unique advantages in noisy environments or when communicating with individuals with speech impairments. However, this technology still faces challenges, such as limited generalization ability due to different speech habits, high recognition error rates caused by confusable phonemes, and difficulties adapting to complex lighting conditions and facial occlusions. This paper proposes a lip reading data augmentation method-Partition-Time Masking (PTM)-to address these challenges and improve lip reading models' performance and generalization ability. Applying nonlinear transformations to the training data enhances the model's generalization ability when handling diverse speakers and environmental conditions. A lip-reading recognition model architecture, Swin Transformer and 3D Convolution (ST3D), was designed to overcome the limitations of traditional lip-reading models that use ResNet-based front-end feature extraction networks. By adopting a strategy that combines Swin Transformer and 3D convolution, the proposed model enhances performance. To validate the effectiveness of the Partition-Time Masking data augmentation method, experiments were conducted on the LRW video dataset using the DC-TCN model, achieving a peak accuracy of 92.15%. The ST3D model was validated on the LRW and LRW1000 video datasets, achieving a maximum accuracy of 56.1% on the LRW1000 dataset and 91.8% on the LRW dataset, outperforming current mainstream lip reading models and demonstrating superior performance on challenging easily confused samples.
Regional and cultural diversities around the world have given birth to a large number of writing systems and scripts, which consist of varying character sets. Developing an optimal character recognition for such a var...
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Regional and cultural diversities around the world have given birth to a large number of writing systems and scripts, which consist of varying character sets. Developing an optimal character recognition for such a varying and large character set is a challenging task. Unlimited variations in handwritten text due to mood swings, varying writing styles, changes in medium of writing, and many more puzzle the research community. To overcome this problem, researchers have proposed various techniques for the automatic recognition of cursive languages like Urdu, Pashto, and Arabic. With the passage of time, the field of text recognition matured, and the number of publications exponentially increased in the targeted field. It is very difficult to find all the techniques developed, calculate the time and resource consumptions, and understand the cost-benefit tradeoffs among these techniques. These tradeoffs resist making this technology able for practical use. To address these tradeoffs, this article systematic analysis to identify gaps in the literature and suggest new enhanced solution accordingly. A total of 153 of the most relevant articles from 2008 to 2022 are analyzed in this systematic literature review (SLR) work. This systematic review process shows (1) the list of techniques suggested for cursive text recognition purposes and its capabilities, (2) set of feature extraction techniques proposed, and (3) implementation tools used to design and simulate the empirical studies in this specialized field. We have also discussed the emerging trends and described their implications for the research community in this specialized domain. This systematic assessment will ultimately help researchers to perform an overview of the existing character/text recognition approaches, recognition capabilities, and time consumption and subsequently identify the areas that requires a significant attention in the near future.
A family of sets is (p, q) -intersecting if every nonempty subfamily of p or fewer sets has at least q elements in its total intersection. A family of sets has the (p, q)-Helly property if every nonempty (p, q)-inters...
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A family of sets is (p, q) -intersecting if every nonempty subfamily of p or fewer sets has at least q elements in its total intersection. A family of sets has the (p, q)-Helly property if every nonempty (p, q)-intersecting subfamily has total intersection of cardinality at least q. The (2, 1)-Helly property is the usual Helly property. A hypergraph is (p, q)-Helly if its edge family has the (p, q)-Helly property and hereditary (p, q)-Helly if each of its subhypergraphs has the (p, q)-Helly property. A graph is (p, q)-clique-Helly if the family of its maximal cliques has the (p, q)-Helly property and hereditary (p, q)-clique-Helly if each of its induced subgraphs is (p, q)-clique-Helly. The classes of (p, q)-biclique-Helly and hereditary (p, q)-biclique-Helly graphs are defined analogously. In this work, we prove several characterizations of hereditary (p, q)-Helly hypergraphs, including one by minimal forbidden partial subhypergraphs. On the algorithmic side, we give an improved time bound for the recognition of (p, q)-Helly hypergraphs for each fixed q and show that the recognition of hereditary (p, q)-Helly hypergraphs can be solved in polynomial time if p and q are fixed and co-NP-complete if p is part of the input. In addition, we generalize the characterization of p-clique-Helly graphs in terms of expansions to (p, q)-clique-Helly graphs and give different characterizations of hereditary (p, q)-clique-Helly graphs, including one by forbidden induced subgraphs. We give an improvement on the time bound for the recognition of (p, q)-clique-Helly graphs and prove that the recognition problem of hereditary (p, q)-clique-Helly graphs is polynomial-time solvable for p and q fixed and NP-hard if p or q is part of the input. Finally, we provide different characterizations, give recognition algorithms, and prove hardness results for (p, q)-biclique-Helly graphs and hereditary (p, q)-biclique-Helly graphs which are analogous to those for (p, q)-clique-Helly and hereditar
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