Search Results - (( using optimization methods algorithm ) OR ( features extraction learning algorithm ))

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  1. 1

    Genetic algorithm based ensemble framework for sentiment analysis by Lai, Po Hung

    Published 2018
    “…Feature extraction produces various representations of plain text documents whereas feature selection selects the features that are useful and relevant to the classification task. …”
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    Thesis
  2. 2

    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
    “…In this method, permission-based features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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    Article
  3. 3
  4. 4

    Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

    Published 2024
    “…The proposed method integrates colour and texture feature-based image analysis with machine learning algorithms for classification. …”
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    Thesis
  5. 5

    Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem

    Published 2019
    “…A multi-objective feature selection approach comprises of multi-objective binary-valued backtracking search algorithm (MOBBSA) as an efficient evolutionary search algorithm and ANFIS method is developed in this paper to extract the most influential subsets of input variables with maximum relevancy and minimum redundancy. …”
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    Article
  6. 6

    Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

    Published 2021
    “…Also, the current motion target detection algorithms extract features from the relevant object only if the moving object has complex texture features. …”
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    Article
  7. 7

    Context-driven satire detection with deep learning by Razali, Md Saifullah, Abdul Halin, Alfian, Chow, Yang-Wai, Mohd Norowi, Noris, Doraisamy, Shyamala

    Published 2022
    “…It is the study of extracting the most optimal features by using a deep learning architecture combined with carefully handcrafted contextual features. …”
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    Article
  8. 8

    Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

    Published 2017
    “…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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    Thesis
  9. 9

    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

    Published 2024
    “…In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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    Thesis
  10. 10

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

    Published 2016
    “…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
  11. 11

    An optimized multi-layer ensemble framework for sentiment analysis by Lai, Po Hung, Alfred Rayner

    Published 2019
    “…The ensemble concept is applied to all 3 tasks by combining different methods to perform the tasks and combine their results. optimization is performed by using Genetic Algorithm to find the combination of methods that could perform better. …”
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    Conference or Workshop Item
  12. 12

    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
  13. 13

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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    Thesis
  14. 14

    Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm by Iqbal, M.J., Faye, I., Said, A.M.D., Samir, B.B.

    Published 2017
    “…The major problems in classifying protein sequences into existing families/superfamilies are the following: the selection of a suitable sequence encoding method, the extraction of an optimized subset of features that possesses significant discriminatory information, and the adaptation of an appropriate learning algorithm that classifies protein sequences with higher classification accuracy. …”
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    Article
  15. 15

    A COLLABORATIVE FRAMEWORK FOR ANDROID MALWARE IDENTIFICATION USING DYNAMIC ANALYSIS by Thayaaleni, Rajandran

    Published 2019
    “…The scope of this project focuses on Android Malware detection by using dynamic analysis. The methods to implement this project is through data collection, feature extraction, feature selection, and classification process. …”
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    Final Year Project Report / IMRAD
  16. 16

    Behavioural Feature Extraction For Context-Aware Traffic Classification Of Mobile Applications by Aun, Yichiet

    Published 2018
    “…This thesis identified domain-specific features that are effective for accurate, large-scale and scalable mobile applications classification using machine learning techniques. This thesis designed a context-aware traffic classification framework that includes a set of sequential algorithms from cleaning datasets, to identifying new features and detecting optimal classifier(s) based on problem contexts to improve classification accuracy in multi-variate traffic classification.…”
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    Thesis
  17. 17

    Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

    Published 2019
    “…The benchmark of the classification algorithm for CA is needed to analyze the optimal output of the algorithm. …”
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    Thesis
  18. 18

    Instant Sign Language Recognition by WAR Strategy Algorithm Based Tuned Machine Learning by Abd Al-Latief S.T., Yussof S., Ahmad A., Khadim S.M., Abdulhasan R.A.

    Published 2025
    “…Afterward, the WAR Strategy optimization algorithm has been adopted in two procedures, first in optimizing the extracted set of features, and second to fine-tune the hyperparameters of six standard machine learning models in order to achieve precise and efficient sign language recognition. …”
    Article
  19. 19

    Noise eliminated ensemble empirical mode decomposition scalogram analysis for rotating machinery fault diagnosis by Atik, Faysal

    Published 2022
    “…Artificial intelligence can be applied in fault feature extraction and classification. It is crucial to use an effective feature extraction method to obtain most of the fault information and a robust classifier to classify those features. …”
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    Thesis
  20. 20

    A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal by Aymen Taher , Ahmed al-Ashwal

    Published 2019
    “…Lastly, the incremental learning algorithm ABACOC is used to classify each feature of food classes. …”
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    Thesis