Search Results - (( data classification using algorithm ) OR ( pattern extraction using algorithm ))

Search alternatives:

Refine Results
  1. 1
    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier

    Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier by Siow, Shien Loong

    Published 2018
    “…Classic local binary pattern (LBP) is one of the most useful feature extraction methods. …”
    Get full text
    Get full text
    Monograph
    Save to List
    Saved in:
  2. 2
    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  3. 3
    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM

    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, khan

    Published 2011
    “…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
    Get full text
    Get full text
    Citation Index Journal
    Save to List
    Saved in:
  4. 4
    Pattern Recognition for Human Diseases Classification in Spectral Analysis

    Pattern Recognition for Human Diseases Classification in Spectral Analysis by Nur Hasshima Hasbi, Abdullah Bade, Fuei, Pien Chee, Muhammad Izzuddin Rumaling

    Published 2022
    “…On the other hand, classification methods are techniques or algorithms used to group samples into a predetermined category. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  5. 5
    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC

    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

    Published 2014
    “…Automated system also saves time and cost as the system is able to process large amount of image data at one time. This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
    Get full text
    Get full text
    Final Year Project
    Save to List
    Saved in:
  6. 6
    Songket pattern classification using backpropagation neural network / Nik Aidil Syawalni Nik Mazlan

    Songket pattern classification using backpropagation neural network / Nik Aidil Syawalni Nik Mazlan by Nik Mazlan, Nik Aidil Syawalni

    Published 2024
    “…The process included data pre-processing and feature extraction. The BPNN algorithm was implemented to proficiently identify and classify Songket pattern, and the evaluation involved analyzing predicted results with different data splitting ratios, such as 70:30 and 80:20. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  7. 7
    Classification for large number of variables with two imbalanced groups

    Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

    Published 2020
    “…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  8. 8
    Improved GART neural network model for pattern classification and rule extraction with application to power systems

    Improved GART neural network model for pattern classification and rule extraction with application to power systems by Yap K.S., Lim C.P., Au M.T.

    Published 2023
    “…IGART enhances the dynamics of GART in several aspects, which include the use of the Laplacian likelihood function, a new vigilance function, a new match-tracking mechanism, an ordering algorithm for determining the sequence of training data, and a rule extraction capability to elicit if-then rules from the network. …”
    Article
    Save to List
    Saved in:
  9. 9
    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani

    A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

    Published 2016
    “…Various data mining techniques are being used by researchers of different domains to analyze data and extract valuable information from a data set for further use. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  10. 10
    Waste classification using support vector machine with SIFT-PCA feature extraction

    Waste classification using support vector machine with SIFT-PCA feature extraction by Puspaningrum, Adita Putri, Endah, Sukmawati Nur, Sasongko, Priyo Sidik, Kusumaningrum, Retno, ., Khadijah, ., Rismiyati, Ernawan, Ferda

    Published 2020
    “…This research proposes waste image classification to support automatic waste sorting using Support Vector Machine (SVM) classification algorithm and SIFT-PCA (Scale Invariant Feature Transform - Principal Component Analysis) feature extraction. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  11. 11
    An extended ID3 decision tree algorithm for spatial data

    An extended ID3 decision tree algorithm for spatial data by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

    Published 2011
    “…It is because spatial data mining algorithms have to consider not only objects of interest itself but also neighbours of the objects in order to extract useful and interesting patterns. …”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  12. 12
    Classification and detection of intelligent house resident activities using multiagent

    Classification and detection of intelligent house resident activities using multiagent by ,, Mohd. Marufuzzaman, M. B. I., Raez, M. A. M., Ali, Rahman, Labonnah F.

    Published 2013
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  13. 13
    HEp-2 cell images classification based on statistical texture analysis and fuzzy logic

    HEp-2 cell images classification based on statistical texture analysis and fuzzy logic by Jamil, N.F.B., Faye, I., May, Z.

    Published 2014
    “…This paper proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  14. 14
    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter

    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

    Published 2019
    “…This is taking advantage on the discriminative feature provided by both methods, statistical and CSP filter, which is expected to increase the accuracy of the eye state classification algorithm. The process of developing the EEG eye state classification algorithm, includes data extraction, pre-processing, data normalization, feature extraction, feature selection and classification are detailed out in this paper. …”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  15. 15
    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter

    EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter by Woon, W.C., Yahya, N., Badruddin, N.

    Published 2019
    “…This is taking advantage on the discriminative feature provided by both methods, statistical and CSP filter, which is expected to increase the accuracy of the eye state classification algorithm. The process of developing the EEG eye state classification algorithm, includes data extraction, pre-processing, data normalization, feature extraction, feature selection and classification are detailed out in this paper. …”
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  16. 16
    Development of a scaled conjugate gradient algorithm for significant RF neural signal processing

    Development of a scaled conjugate gradient algorithm for significant RF neural signal processing by Mohd Norden, Muhammad Farid Akmal, Mohd Isa, Roshakimah, Mohd Isa, Mohd Roshalizi, S. Abdul Kadir, Ros Shilawani, Md Azli, Muhammad Hariz, Muhammad Akram, Amir Syarif

    Published 2025
    “…SCG improves the learning process of ANNs by speeding up the adjustment of their internal weights, helping the network learn faster and more accurately from large data sets. This study aims to improve the classification of RF neural data patterns using SCG. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  17. 17
    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition

    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

    Published 2004
    “…The algorithm enhances the recognition ability of the system compared to manual extraction and labeling of pattern classes. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  18. 18
    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm

    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm by Ali, M., Jung, L.T., Abdel-Aty, A.-H., Abubakar, M.Y., Elhoseny, M., Ali, I.

    Published 2020
    “…The k-NN algorithm is one of the most renowned ML algorithms widely used in the area of data classification research. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  19. 19
    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm

    Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm by Ali, M., Jung, L.T., Abdel-Aty, A.-H., Abubakar, M.Y., Elhoseny, M., Ali, I.

    Published 2020
    “…The k-NN algorithm is one of the most renowned ML algorithms widely used in the area of data classification research. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  20. 20
    Improved building roof type classification using correlation-based feature selection and gain ratio algorithms

    Improved building roof type classification using correlation-based feature selection and gain ratio algorithms by Norman, M., Mohd Shafri, Helmi Zulhaidi, Pradhan, Biswajeet, Yusuf, B.

    Published 2017
    “…Of late, application of data mining for pattern recognition and feature classification is fast becoming an essential technique in remote sensing research. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:

Search Tools: