Search Results - (( code classification matching algorithm ) OR ( java generation matching algorithm ))
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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding
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
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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Message based random variable length key encryption algorithm.
Published 2009“…Encryption and decryption times measured between 5 and 27 m sec in 2 GHz Pentium and java platform so time variant and fast enough key generation had been kept collision and timing attacks away due to small seized storage. …”
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Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite
Published 2025“…Experimental results indicate that WOA outperforms or matches the effectiveness of these strategies in generating smaller test suites, particularly for higher interaction strengths. …”
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Securing cloud data system (SCDS) for key exposure using AES algorithm
Published 2021“…The website tested by many users that use to register and upload them own data and files using them own e-mails and the unique key that generated after completing the registration. We used to insure for the users data and files in our website by checking the process of our generated system (SCDS) and we got match results for the same files in case of encryption and decryption process.…”
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Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali
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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