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Search Results (12)
  • Open Access

    ARTICLE

    Supervised Feature Learning for Offline Writer Identification Using VLAD and Double Power Normalization

    Dawei Liang1,2,4, Meng Wu1,*, Yan Hu3

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 279-293, 2023, DOI:10.32604/cmc.2023.035279 - 08 June 2023

    Abstract As an indispensable part of identity authentication, offline writer identification plays a notable role in biology, forensics, and historical document analysis. However, identifying handwriting efficiently, stably, and quickly is still challenging due to the method of extracting and processing handwriting features. In this paper, we propose an efficient system to identify writers through handwritten images, which integrates local and global features from similar handwritten images. The local features are modeled by effective aggregate processing, and global features are extracted through transfer learning. Specifically, the proposed system employs a pre-trained Residual Network to mine the relationship… More >

  • Open Access

    ARTICLE

    Degree-Based Entropy Descriptors of Graphenylene Using Topological Indices

    M. C. Shanmukha1, Sokjoon Lee2,*, A. Usha3, K. C. Shilpa4, Muhammad Azeem5

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 939-964, 2023, DOI:10.32604/cmes.2023.027254 - 23 April 2023

    Abstract Graph theory plays a significant role in the applications of chemistry, pharmacy, communication, maps, and aeronautical fields. The molecules of chemical compounds are modelled as a graph to study the properties of the compounds. The geometric structure of the compound relates to a few physical properties such as boiling point, enthalpy, π-electron energy, molecular weight. The article aims to determine the practical application of graph theory by solving one of the interdisciplinary problems describing the structures of benzenoid hydrocarbons and graphenylene. The topological index is an invariant of a molecular graph associated with the chemical More >

  • Open Access

    ARTICLE

    Topological Aspects of Dendrimers via Connection-Based Descriptors

    Muhammad Javaid1, Ahmed Alamer2, Aqsa Sattar1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1649-1667, 2023, DOI:10.32604/cmes.2022.022832 - 27 October 2022

    Abstract Topological indices (TIs) have been practiced for distinct wide-ranging physicochemical applications, especially used to characterize and model the chemical structures of various molecular compounds such as dendrimers, nanotubes and neural networks with respect to their certain properties such as solubility, chemical stability and low cytotoxicity. Dendrimers are prolonged artificially synthesized or amalgamated natural macromolecules with a sequential layer of branches enclosing a central core. A present-day trend in mathematical and computational chemistry is the characterization of molecular structure by applying topological approaches, including numerical graph invariants. Among topological descriptors, Zagreb connection indices (ZCIs) have much More >

  • Open Access

    ARTICLE

    Keypoint Description Using Statistical Descriptor with Similarity-Invariant Regions

    Ibrahim El rube'*, Sameer Alsharif

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 407-421, 2022, DOI:10.32604/csse.2022.022400 - 02 December 2021

    Abstract This article presents a method for the description of key points using simple statistics for regions controlled by neighboring key points to remedy the gap in existing descriptors. Usually, the existent descriptors such as speeded up robust features (SURF), Kaze, binary robust invariant scalable keypoints (BRISK), features from accelerated segment test (FAST), and oriented FAST and rotated BRIEF (ORB) can competently detect, describe, and match images in the presence of some artifacts such as blur, compression, and illumination. However, the performance and reliability of these descriptors decrease for some imaging variations such as point of… More >

  • Open Access

    ARTICLE

    Reactions’ Descriptors Selection and Yield Estimation Using Metaheuristic Algorithms and Voting Ensemble

    Olutomilayo Olayemi Petinrin1, Faisal Saeed2, Xiangtao Li1, Fahad Ghabban2, Ka-Chun Wong1,3,*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4745-4762, 2022, DOI:10.32604/cmc.2022.020523 - 11 October 2021

    Abstract Bioactive compounds in plants, which can be synthesized using N-arylation methods such as the Buchwald-Hartwig reaction, are essential in drug discovery for their pharmacological effects. Important descriptors are necessary for the estimation of yields in these reactions. This study explores ten metaheuristic algorithms for descriptor selection and model a voting ensemble for evaluation. The algorithms were evaluated based on computational time and the number of selected descriptors. Analyses show that robust performance is obtained with more descriptors, compared to cases where fewer descriptors are selected. The essential descriptor was deduced based on the frequency of More >

  • Open Access

    ARTICLE

    Enhancing Scalability of Image Retrieval Using Visual Fusion of Feature Descriptors

    S. Balammal@Geetha*, R. Muthukkumar, V. Seenivasagam

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1737-1752, 2022, DOI:10.32604/iasc.2022.018822 - 09 October 2021

    Abstract Content-Based Image Retrieval (CBIR) is an approach of retrieving similar images from a large image database. Recently CBIR poses new challenges in semantic categorization of the images. Different feature extraction technique have been proposed to overcome the semantic breach problems, however these methods suffer from several shortcomings. This paper contributes an image retrieval system to extract the local features based on the fusion of scale-invariant feature transform (SIFT) and KAZE. The strength of local feature descriptor SIFT complements global feature descriptor KAZE. SIFT concentrates on the complete region of an image using high fine points… More >

  • Open Access

    ARTICLE

    A Study of Cellular Neural Networks with Vertex-Edge Topological Descriptors

    Sadia Husain1, Muhammad Imran2,*, Ali Ahmad1, Yasir Ahmad1, Kashif Elahi3

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3433-3447, 2022, DOI:10.32604/cmc.2022.020384 - 27 September 2021

    Abstract The Cellular Neural Network (CNN) has various parallel processing applications, image processing, non-linear processing, geometric maps, high-speed computations. It is an analog paradigm, consists of an array of cells that are interconnected locally. Cells can be arranged in different configurations. Each cell has an input, a state, and an output. The cellular neural network allows cells to communicate with the neighbor cells only. It can be represented graphically; cells will represent by vertices and their interconnections will represent by edges. In chemical graph theory, topological descriptors are used to study graph structure and their biological More >

  • Open Access

    ARTICLE

    On Vertex-Edge-Degree Topological Descriptors for Certain Crystal Networks

    Sadia Husain1, Fouad A. Abolaban2, Ali Ahmad1, Muhammad Ahsan Asim1, Yasir Ahmad1

    Computer Systems Science and Engineering, Vol.40, No.3, pp. 835-850, 2022, DOI:10.32604/csse.2022.018534 - 24 September 2021

    Abstract Due to the combinatorial nature of graphs they are used easily in pure sciences and social sciences. The dynamical arrangement of vertices and their associated edges make them flexible (like liquid) to attain the shape of any physical structure or phenomenon easily. In the field of ICT they are used to reflect distributed component and communication among them. Mathematical chemistry is another interesting domain of applied mathematics that endeavors to display the structure of compounds that are formed in result of chemical reactions. This area attracts the researchers due to its applications in theoretical and… More >

  • Open Access

    ARTICLE

    Comparison of Local Descriptors for Humanoid Robots Localization Using a Visual Bag of Words Approach

    Noé G. Aldana-Murillo, Jean-Bernard Hayet, Héctor M. Becerra

    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 471-481, 2018, DOI:10.1080/10798587.2017.1304508

    Abstract In this paper, we address the problem of the appearance-based localization of a humanoid robot, in the context of robot navigation. We only use information obtained by a single sensor, in this case the camera mounted on the robot. We aim at determining the most similar image within a previously acquired set of key images (also referred to as a visual memory) to the current view of the monocular camera carried by the robot. The robot is initially kidnapped and the current image has to be compared with the visual memory. To solve this problem, More >

  • Open Access

    ARTICLE

    Analyzing digital color descriptors in wheat

    Salomón N1, V Misller1, C Delrieux2, R Miranda3

    Phyton-International Journal of Experimental Botany, Vol.84, No.2, pp. 306-311, 2015, DOI:10.32604/phyton.2015.84.306

    Abstract Color is one of the factors used in quality estimation in many agricultural and food products. Currently, the evaluation of color depends on judgments made by human experts. These are subjective and inevitably affected by physical, physiological and environmental conditions. Suitable instrumental is required to provide objectivity and coherence to color measurements and quantitative expressions. It would be very useful to have tools that allow both practical and precise approaches to chromatic evaluation of products for human consumption. This work suggests a methodology which might contribute to solve that constraint and the analysis of environmental… More >

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