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  • Open Access

    ARTICLE

    Webpage Matching Based on Visual Similarity

    Mengmeng Ge1, Xiangzhan Yu1,*, Lin Ye1,2, Jiantao Shi1

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3393-3405, 2022, DOI:10.32604/cmc.2022.017220

    Abstract With the rapid development of the Internet, the types of webpages are more abundant than in previous decades. However, it becomes severe that people are facing more and more significant network security risks and enormous losses caused by phishing webpages, which imitate the interface of real webpages and deceive the victims. To better identify and distinguish phishing webpages, a visual feature extraction method and a visual similarity algorithm are proposed. First, the visual feature extraction method improves the Vision-based Page Segmentation (VIPS) algorithm to extract the visual block and calculate its signature by perceptual hash technology. Second, the visual similarity… 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

    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 view, zoom (scale), and rotation.… More >

  • Open Access

    ARTICLE

    Towards Improving Predictive Statistical Learning Model Accuracy by Enhancing Learning Technique

    Ali Algarni1, Mahmoud Ragab2,3,4,*, Wardah Alamri5, Samih M. Mostafa6

    Computer Systems Science and Engineering, Vol.42, No.1, pp. 303-318, 2022, DOI:10.32604/csse.2022.022152

    Abstract The accuracy of the statistical learning model depends on the learning technique used which in turn depends on the dataset’s values. In most research studies, the existence of missing values (MVs) is a vital problem. In addition, any dataset with MVs cannot be used for further analysis or with any data driven tool especially when the percentage of MVs are high. In this paper, the authors propose a novel algorithm for dealing with MVs depending on the feature selection (FS) of similarity classifier with fuzzy entropy measure. The proposed algorithm imputes MVs in cumulative order. The candidate feature to be… More >

  • Open Access

    ARTICLE

    Similarity Analytic Solutions of a 3D-Fractal Nanofluid Uncoupled System Optimized by a Fractal Symmetric Tangent Function

    Rabha W. Ibrahim1,*, Ahmed M. Ajaj2, Nadia M.G. Al-Saidi3, Dumitru Balean4,5,6

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 221-232, 2022, DOI:10.32604/cmes.2022.018348

    Abstract The science of strategy (game theory) is known as the optimal decision-making of autonomous and challenging players in a strategic background. There are different strategies to complete the optimal decision. One of these strategies is the similarity technique. Similarity technique is a generalization of the symmetric strategy, which depends only on the other approaches employed, which can be formulated by altering diversities. One of these methods is the fractal theory. In this investigation, we present a new method studying the similarity analytic solution (SAS) of a 3D-fractal nanofluid system (FNFS). The dynamic evolution is completely given by the concept of… More >

  • Open Access

    ARTICLE

    INTS-MFS: A novel method to predict microRNA-disease associations by integrating network topology similarity and microRNA function similarity

    BUWEN CAO1,*, JIAWEI LUO2,*, SAINAN XIAO1, KAI ZHAO1, SHULING YANG1

    BIOCELL, Vol.46, No.3, pp. 837-845, 2022, DOI:10.32604/biocell.2022.017538

    Abstract Identifying associations between microRNAs (miRNAs) and diseases is very important to understand the occurrence and development of human diseases. However, these existing methods suffer from the following limitation: first, some disease-related miRNAs are obtained from the miRNA functional similarity networks consisting of heterogeneous data sources, i.e., disease similarity, protein interaction network, gene expression. Second, little approaches infer disease-related miRNAs depending on the network topological features without the functional similarity of miRNAs. In this paper, we develop a novel model of Integrating Network Topology Similarity and MicroRNA Function Similarity (INTS-MFS). The integrated miRNA similarities are calculated based on miRNA functional similarity… More >

  • Open Access

    ARTICLE

    An Analysis of Perceptual Confusions on Logatome Utterances for Similar Language

    Nur-Hana Samsudin1,*, Mark Lee2

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1025-1039, 2022, DOI:10.32604/iasc.2022.022180

    Abstract In a polyglot speech synthesis, it is possible to use one language resource for another language. However, if the adaptation is not implemented carefully, the foreignness of the sound will be too noticeable for the listeners. This paper presents the analysis of respondents’ acceptance of a series of listening tests. The research goal was to find out in the absence of phonemes of a particular language, would it be possible for the phonemes to be replaced with another language’s phonemes. This will be especially beneficial for under-resourced language either in the case for 1) the language has not yet well… More >

  • Open Access

    ARTICLE

    Profile and Rating Similarity Analysis for Recommendation Systems Using Deep Learning

    Lakshmi Palaniappan1,*, K. Selvaraj2

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 903-917, 2022, DOI:10.32604/csse.2022.020670

    Abstract Recommendation systems are going to be an integral part of any E-Business in near future. As in any other E-business, recommendation systems also play a key role in the travel business where the user has to be recommended with a restaurant that best suits him. In general, the recommendations to a user are made based on similarity that exists between the intended user and the other users. This similarity can be calculated either based on the similarity between the user profiles or the similarity between the ratings made by the users. First phase of this work concentrates on experimentally analyzing… More >

  • Open Access

    ARTICLE

    Denoising Letter Images from Scanned Invoices Using Stacked Autoencoders

    Samah Ibrahim Alshathri1,*, Desiree Juby Vincent2, V. S. Hari2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1371-1386, 2022, DOI:10.32604/cmc.2022.022458

    Abstract Invoice document digitization is crucial for efficient management in industries. The scanned invoice image is often noisy due to various reasons. This affects the OCR (optical character recognition) detection accuracy. In this paper, letter data obtained from images of invoices are denoised using a modified autoencoder based deep learning method. A stacked denoising autoencoder (SDAE) is implemented with two hidden layers each in encoder network and decoder network. In order to capture the most salient features of training samples, a undercomplete autoencoder is designed with non-linear encoder and decoder function. This autoencoder is regularized for denoising application using a combined… More >

  • Open Access

    ARTICLE

    Benchmarking Performance of Document Level Classification and Topic Modeling

    Muhammad Shahid Bhatti1,*, Azmat Ullah1, Rohaya Latip2, Abid Sohail1, Anum Riaz1, Rohail Hassan3

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 125-141, 2022, DOI:10.32604/cmc.2022.020083

    Abstract Text classification of low resource language is always a trivial and challenging problem. This paper discusses the process of Urdu news classification and Urdu documents similarity. Urdu is one of the most famous spoken languages in Asia. The implementation of computational methodologies for text classification has increased over time. However, Urdu language has not much experimented with research, it does not have readily available datasets, which turn out to be the primary reason behind limited research and applying the latest methodologies to the Urdu. To overcome these obstacles, a medium-sized dataset having six categories is collected from authentic Pakistani news… More >

  • Open Access

    ARTICLE

    Brain Image Classification Using Time Frequency Extraction with Histogram Intensity Similarity

    Thangavel Renukadevi1,*, Kuppusamy Saraswathi1, P. Prabu2, K. Venkatachalam3

    Computer Systems Science and Engineering, Vol.41, No.2, pp. 645-460, 2022, DOI:10.32604/csse.2022.020810

    Abstract Brain medical image classification is an essential procedure in Computer-Aided Diagnosis (CAD) systems. Conventional methods depend specifically on the local or global features. Several fusion methods have also been developed, most of which are problem-distinct and have shown to be highly favorable in medical images. However, intensity-specific images are not extracted. The recent deep learning methods ensure an efficient means to design an end-to-end model that produces final classification accuracy with brain medical images, compromising normalization. To solve these classification problems, in this paper, Histogram and Time-frequency Differential Deep (HTF-DD) method for medical image classification using Brain Magnetic Resonance Image… More >

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