Search Results - (( based extraction method algorithm ) OR ( using vectorization learning algorithm ))

Refine Results
  1. 1

    Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

    Published 2008
    “…Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. …”
    Get full text
    Get full text
    Article
  2. 2

    Extreme learning machine classification of file clusters for evaluating content-based feature vectors by Ali, Rabei Raad, Mohamad, Kamaruddin Malik, Jamel, Sapiee, Ahmad Khalid, Shamsul Kamal

    Published 2018
    “…Consequently, an Extreme Learning Machine (ELM) neural network algorithm is used to evaluate the performance of the three methods in which it classifies the class label of the feature vectors to JPEG and Non-JPEG images for files in different file formats. …”
    Get full text
    Article
  3. 3

    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. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  4. 4

    Building extraction of worldview3 imagery via support vector machine using scikit-learn module / Najihah Ismail by Ismail, Najihah

    Published 2021
    “…Moreover, the capability of the programming based using python for building extraction can be assessed. …”
    Get full text
    Get full text
    Thesis
  5. 5

    Herbs recognition based on chemical properties using machine learning algorithm by Mohamad Radzi, Nur Fadzilah, Che Soh, Azura, Ishak, Asnor Juraiza, Hassan, Mohd Khair

    Published 2023
    “…This method has demonstrated promising results in identifying herb species, and the classification method based on machine learning algorithms has proven successful in recognizing and distinguishing herb species…”
    Get full text
    Get full text
    Article
  6. 6

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This work employed the use of machine learning approach. Four conventional classification algorithms: naïve bayes (NB), support vector machines (SVM), nearest neighbor (k-NN), and decision trees (J48) classifiers are implemented in identifying and categorizing tweet data of three political figures in Malaysia: Dato Seri Anwar, Dato Hadi Awang, and Lim Guang Eng, as either positive, negative, or neutral perceptions. …”
    Get full text
    Get full text
    Get full text
    Thesis
  7. 7

    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. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  8. 8

    Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine by Fathi Mahdi Elsiddig Haroun, Mr.

    Published 2023
    “…In this dissertation, a new vegetation encroachment detection method was proposed by studying the feasibility of using the visible-light band of highresolution satellite images using the RetinaNet deep learning model and Support Vector Machine algorithm (SVM). …”
    text::Thesis
  9. 9

    An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

    Published 2025
    “…Traditional machine learning algorithms, such as Decision Trees, Naive Bayes, Random Forest, Random Trees, Multi-Layer Perceptron, and Support Vector Machines, have been extensively applied to address these threats. …”
    Get full text
    Get full text
    Get full text
    Thesis
  10. 10
  11. 11

    A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

    Published 2020
    “…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
    Get full text
    Get full text
    Get full text
    Thesis
  13. 13

    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
    Get full text
    Get full text
    Thesis
  14. 14

    The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

    Published 2021
    “…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
    Get full text
    Get full text
    Thesis
  15. 15

    Feature extraction and supervised learning for volatile organic compounds gas recognition by Mohd Tombel, Nor Syahira, Mohd Zaki, Hasan Firdaus, Mohd Fadglullah, Hanna Farihin

    Published 2023
    “…This research project aims to investigate effective feature extraction techniques that can be employed as discriminative features for machine learning algorithms. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    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.…”
    Get full text
    Get full text
    Thesis
  17. 17

    ANALYSIS OF BIOSENSOR PHYSIOLOGICAL SIGNALS FOR ASSESSMENT OF NEUROLOGICAL STATUS by QIAN XIN, SOONG

    Published 2018
    “…The extracted features are then fed into the Support Vector Machines (SVM) as well as the Ensemble Classifier which is a supervised learning model with associated learning algorithm that helps us to analyze the data for classification of neurological status of the subjects. …”
    Get full text
    Get full text
    Final Year Project
  18. 18

    Design of Predictive Model for TCM Tongue Diagnosis In Malaysia Using Machine Learning by Koe, Jia Chi

    Published 2020
    “…Six supervised machine learning algorithms (Linear Regression, Logistic Regression, K Nearest Neighbors (KNN), Decision Trees (DT), Support Vector Machine (SVM) and Random Forest) are used to perform disease prediction. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  19. 19

    High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor by Abdul Rashid, Raghdah Rasyidah, Shaharudin, Shazlyn Milleana, Sulaiman, Nurul Ainina Filza, Zainuddin, Nurul Hila, Mahdin, Hairulnizam, Mohd Najib, Summayah Aimi, Hidayat, Rahmat

    Published 2024
    “…These factors include identifying relevant atmospheric features contributing to rainfall, addressing missing data, and developing a significant model to predict daily rainfall intensity using appropriate machine-learning techniques. The Principal Component Analysis (PCA) technique was employed to choose relevant environmental variables as input for the machine learning model, and various imputation methods were utilized to manage missing data, such as mean imputation and the KNN algorithm. …”
    Get full text
    Get full text
    Article
  20. 20

    Human hearing disorder recognition model using eeg-aep based signal by Md Nahidul, Islam

    Published 2022
    “…Then, the extracted feature was classified using machine learning and deep learning algorithms. …”
    Get full text
    Get full text
    Thesis