Search Results - (( model identification using algorithm ) OR ( code classifications using algorithm ))

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  1. 1

    An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

    Published 2020
    “…Current work adopts the Fuzzy c-means Bag of Visual Words model and sparse coding for plant identification. …”
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    Article
  2. 2

    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…The combination of gist, MTH and SIFT features increased the performance of image identification and showed 49% accuracy. Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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    Thesis
  3. 3

    Machine learning-based enhanced deep packet inspection for IP packet priority classification with differentiated services code point for advance network management by Khan, Fazeel Ahmed, Abubakar, Adamu

    Published 2024
    “…This study presents an approach to enhance intelligent packet forwarding priority classification on Differentiated Services Code Point (DSCP), leveraging classifiers from machine learning algorithms for Deep Packet Inspection (DPI). …”
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    Article
  4. 4

    Modelling of clinical risk groups (CRGs) classification using FAM by Mohd. Asi, Salina, Saad, Puteh

    Published 2006
    “…FAM is a fast learning algorithm and used less epoch training [4]. Based on its performance in doing the classification, FAM is theoretically suitable to do the CRGs classification. …”
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    Conference or Workshop Item
  5. 5

    Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

    Published 2020
    “…In order to further validate the position of the tagging in the pallet box of the Random Forest model developed, a different predefined location was used to validate the model. …”
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    Thesis
  6. 6

    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2014
    “…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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    Proceeding Paper
  7. 7

    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2015
    “…However, supervised learning technique has limitations for malware classification task. This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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    Article
  8. 8

    Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection by Ahmed Khan, Fazeel, Abubakar, Adamu

    Published 2024
    “…This study develops and analyze using neural network-based models for effective classification of data packets using the DSCP header field. …”
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    Article
  9. 9

    Source code classification using latent semantic indexing with structural and frequency term weighting by Yusof, Yuhanis, Alhersh, Taha, Mahmuddin, Massudi, Mohamed Din, Aniza

    Published 2012
    “…Furthermore,it is also learned that the use of structural information in the weighting scheme contribute to a better classification.…”
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    Article
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    Chain coding and pre processing stages of handwritten character image file by Suliman, Azizah, Sulaiman, Md. Nasir, Othman, Mohamed, O. K. Rahmat, Rahmita Wirza

    Published 2010
    “…This paper discusses in detail some of the algorithms used in the pre-processing stages of an offline handwritten character image file. …”
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    Article
  12. 12

    Hybrid DE-PEM algorithm for identification of UAV helicopter by Tijani, Ismaila, Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus, Abdul Muthalif, Asan Gani

    Published 2014
    “…Design/methodology/approach – In this study, flight data were collected and analyzed; MATLAB-based system identification algorithm was developed using DE and PEM; parameterized state-space model parameters were estimated using the developed algorithm and model dynamic analysis. …”
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    Article
  13. 13
  14. 14

    Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification by Nisar, Humaira, Malik, Aamir Saeed, Choi, Tae-Sun

    Published 2012
    “…This is the basis of the proposed algorithm. The proposed algorithm involves a multistage approach that includes motion vector prediction and motion classification using the characteristics of video sequences. …”
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    Article
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    Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition by Muhammad Arif, Mohamad, Zalili, Musa, Amelia Ritahani, Ismail

    Published 2023
    “…The algorithm experiments are carried out using the chain code representation created from previous research of the Centre of Excellence for Document Analysis and Recognition (CEDAR) dataset, which consists of 126 upper-case letter characters. …”
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    Conference or Workshop Item
  17. 17

    Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2002
    “…The development of a multivariable system identification model for dynamic discrete-time nonlinear system using genetic algorithm was discussed and analysed. …”
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    Conference or Workshop Item
  18. 18

    Multivariable system identification for dynamic discrete-time nonlinear system using genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

    Published 2002
    “…The development of a multivariable system identification model for dynamic discrete-time nonlinear system using genetic algorithm was discussed and analysed. …”
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    Conference or Workshop Item
  19. 19

    Maldroid- attribute selection analysis for malware classification by Rahiwan Nazar, Romli, Mohamad Fadli, Zolkipli, Mohd Zamri, Osman

    Published 2019
    “…Hence, the objective of this paper is to find the most effective and efficient attribute selection and classification algorithm in malware detection. Moreover, in order to get the best combination between attribute selection and classification algorithm, eight attributes selection and seven categories machine learning algorithm are applied in this study. …”
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    Article
  20. 20

    Identification of non-linear dynamic systems using fuzzy system with constrained membership functions by Yaakob, Mohd. Shafiek

    Published 2004
    “…Main research directions in this field include the complexity reduction of fuzzy models models, structure identification of fuzzy system, and application of new or improved training algorithms. …”
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    Thesis