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  • Open Access

    ARTICLE

    Research on Feature Matching Optimization Algorithm for Automotive Panoramic Surround View System

    Guangbing Xiao*, Ruijie Gu, Ning Sun, Yong Zhang

    Computer Systems Science and Engineering, Vol.48, No.5, pp. 1329-1348, 2024, DOI:10.32604/csse.2024.050817 - 13 September 2024

    Abstract In response to the challenges posed by insufficient real-time performance and suboptimal matching accuracy of traditional feature matching algorithms within automotive panoramic surround view systems, this paper has proposed a high-performance dimension reduction parallel matching algorithm that integrates Principal Component Analysis (PCA) and Dual-Heap Filtering (DHF). The algorithm employs PCA to map the feature points into the lower-dimensional space and employs the square of Euclidean distance for feature matching, which significantly reduces computational complexity. To ensure the accuracy of feature matching, the algorithm utilizes Dual-Heap Filtering to filter and refine matched point pairs. To further More >

  • Open Access

    ARTICLE

    Novelty of Different Distance Approach for Multi-Criteria Decision-Making Challenges Using q-Rung Vague Sets

    Murugan Palanikumar1, Nasreen Kausar2,*, Dragan Pamucar3,4, Seifedine Kadry5,6,7,*, Chomyong Kim8, Yunyoung Nam9

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3353-3385, 2024, DOI:10.32604/cmes.2024.031439 - 11 March 2024

    Abstract In this article, multiple attribute decision-making problems are solved using the vague normal set (VNS). It is possible to generalize the vague set (VS) and q-rung fuzzy set (FS) into the q-rung vague set (VS). A log q-rung normal vague weighted averaging (log q-rung NVWA), a log q-rung normal vague weighted geometric (log q-rung NVWG), a log generalized q-rung normal vague weighted averaging (log Gq-rung NVWA), and a log generalized q-rung normal vague weighted geometric (log Gq-rung NVWG) operator are discussed in this article. A description is provided of the scoring function, accuracy function and operational laws of the log q-rung… More >

  • Open Access

    ARTICLE

    A Novel Classification Method with Cubic Spline Interpolation

    Husam Ali Abdulmohsin1,*, Hala Bahjat Abdul Wahab2, Abdul Mohssen Jaber Abdul Hossen3

    Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 339-355, 2022, DOI:10.32604/iasc.2022.018045 - 03 September 2021

    Abstract Classification is the last, and usually the most time-consuming step in recognition. Most recently proposed classification algorithms have adopted machine learning (ML) as the main classification approach, regardless of time consumption. This study proposes a statistical feature classification cubic spline interpolation (FC-CSI) algorithm to classify emotions in speech using a curve fitting technique. FC-CSI is utilized in a speech emotion recognition system (SERS). The idea is to sketch the cubic spline interpolation (CSI) for each audio file in a dataset and the mean cubic spline interpolations (MCSIs) representing each emotion in the dataset. CSI interpolation… More >

  • Open Access

    ARTICLE

    Performances of K-Means Clustering Algorithm with Different Distance Metrics

    Taher M. Ghazal1,2, Muhammad Zahid Hussain3, Raed A. Said5, Afrozah Nadeem6, Mohammad Kamrul Hasan1, Munir Ahmad7, Muhammad Adnan Khan3,4,*, Muhammad Tahir Naseem3

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 735-742, 2021, DOI:10.32604/iasc.2021.019067 - 11 August 2021

    Abstract Clustering is the process of grouping the data based on their similar properties. Meanwhile, it is the categorization of a set of data into similar groups (clusters), and the elements in each cluster share similarities, where the similarity between elements in the same cluster must be smaller enough to the similarity between elements of different clusters. Hence, this similarity can be considered as a distance measure. One of the most popular clustering algorithms is K-means, where distance is measured between every point of the dataset and centroids of clusters to find similar data objects and More >

  • Open Access

    ARTICLE

    Generalized Normalized Euclidean Distance Based Fuzzy Soft Set Similarity for Data Classification

    Rahmat Hidayat1,2,*, Iwan Tri Riyadi Yanto1,3, Azizul Azhar Ramli1, Mohd Farhan Md. Fudzee1, Ansari Saleh Ahmar4

    Computer Systems Science and Engineering, Vol.38, No.1, pp. 119-130, 2021, DOI:10.32604/csse.2021.015628 - 01 April 2021

    Abstract

    Classification is one of the data mining processes used to predict predetermined target classes with data learning accurately. This study discusses data classification using a fuzzy soft set method to predict target classes accurately. This study aims to form a data classification algorithm using the fuzzy soft set method. In this study, the fuzzy soft set was calculated based on the normalized Hamming distance. Each parameter in this method is mapped to a power set from a subset of the fuzzy set using a fuzzy approximation function. In the classification step, a generalized normalized Euclidean

    More >

  • Open Access

    ARTICLE

    Prospect Theory Based Hesitant Fuzzy Multi-Criteria Decision Making for Low Sulphur Fuel of Maritime Transportation

    Changli Lu1, Ming Zhao1,2, Imran Khan3, Peerapong Uthansakul4,*

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1511-1528, 2021, DOI:10.32604/cmc.2020.012556 - 26 November 2020

    Abstract The environmental impact of maritime transport has now become a relevant issue in sustainable policy formulation and has attracted increasing interest from academia. For the sustainable development of maritime transport, International Maritime Organization stipulates that the sulfur content of ship emissions will reach 0.5 from 2020. With the approaching of the stipulated implementation date, shipowners need to adopt scientific methods to make decision on low sulfur fuel. In this study, we applied a prospect theory based hesitant fuzzy multi-criteria decision-making model to obtain the optimal decision of low Sulphur marine fuel. For this purpose, the… More >

  • Open Access

    ARTICLE

    Phishing Detection with Image Retrieval Based on Improved Texton Correlation Descriptor

    Guoyuan Lin1,2,*, Bowen Liu1, Pengcheng Xiao3, Min Lei4, Wei Bi5,6

    CMC-Computers, Materials & Continua, Vol.57, No.3, pp. 533-547, 2018, DOI:10.32604/cmc.2018.03720

    Abstract Anti-detection is becoming as an emerging challenge for anti-phishing. This paper solves the threats of anti-detection from the threshold setting condition. Enough webpages are considered to complicate threshold setting condition when the threshold is settled. According to the common visual behavior which is easily attracted by the salient region of webpages, image retrieval methods based on texton correlation descriptor (TCD) are improved to obtain enough webpages which have similarity in the salient region for the images of webpages. There are two steps for improving TCD which has advantage of recognizing the salient region of images: More >

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