Search Results - (( code classification matching algorithm ) OR ( java implementation matching algorithm ))

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  1. 1

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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    An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

    Published 2020
    “…In the classic Bag of visual words model, the Fuzzy c-means algorithm is replaced with K-means and the accuracy of SIFT matching is increased. …”
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    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…For next, instead of k-means clustring, Fuzzy cmeans clustering is combined with Spatial Pyramid Matching image representation to improve the accuracy of classification results. …”
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    Thesis
  6. 6

    Multi-floor indoor location estimation system based on wireless local area network by Chua, Tien Han

    Published 2007
    “…During location estimation, current histogram of RSS at unknown location will be compared to the database. The most probable match is selected and returned as estimated location based on Bayesian filtering algorithm. …”
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  7. 7

    An Agent-Based System with Personalization and Intelligent Assistance Services for Facilitating Knowledge Sharing by Mohd Sharef, Nurfadhlina

    Published 2006
    “…KSFaci is embedded in web environment and is implemented using Java Servlet and runs under Apache server. …”
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  8. 8

    Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali by M. Ali, Musab A.

    Published 2016
    “…The subsequent step is using the DAUB3 wavelet transform for feature extraction along with the application of an additional step for biometric template security that is the Non-invertible transform (cancelable biometrics method) and finally utilizing the Support Vector Machine (Non-linear Quadratic kernel) for matching/classification. The experimental results showed that the recognition rate achieved are of 99.9% on Bath-A data set, with a maximum decision criterion of 0.97.…”
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