Search Results - (( data applications using algorithm ) OR ( code classification using algorithm ))

Refine Results
  1. 1

    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. …”
    Get full text
    Get full text
    Get full text
    Article
  2. 2
  3. 3
  4. 4
  5. 5

    Improving hand written digit recognition using hybrid feature selection algorithm by Wong, Khye Mun

    Published 2022
    “…While mRMR was capable of identifying a subset of features that were highly relevant to the targeted classification variable, it still carry the weakness of capturing redundant features along with the algorithm. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  6. 6

    Wearable based-sensor fall detection system using machine learning algorithm by Ishak, Anis Nadia, Habaebi, Mohamed Hadi, Yusoff, Siti Hajar, Islam, Md. Rafiqul

    Published 2021
    “…Then, a Machine Learning Algorithm (MLA) is used to train and test the data before a classifier is used to classify the new incoming dataset. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Proceeding Paper
  7. 7

    Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia by San, Limhwee

    Published 2006
    “…The proposed algorithms were used to generate PM10 and AOT maps for the study areas. …”
    Get full text
    Get full text
    Thesis
  8. 8
  9. 9

    Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

    Published 2022
    “…The result from the SVM algorithms will be used as database for the machine learning in Microsoft Azure. …”
    Get full text
    Get full text
    Monograph
  10. 10

    Deep learning based emotion recognition for image and video signals: matlab implementation by Ashraf, Arselan, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2021
    “…This book is carried out to develop an image and video-based emotion recognition model using CNN for automatic feature extraction and classification with Matlab sample codes. …”
    Get full text
    Get full text
    Book
  11. 11

    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. …”
    Get full text
    Get full text
    Conference or Workshop Item
  12. 12

    POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD by HENG KEOW, CHUAH

    Published 2012
    “…Simulation produces satisfactory result in identifying the disturbance and proves that it is possible to use this model for power disturbance classification even in a noisy environment. …”
    Get full text
    Get full text
    Thesis
  13. 13

    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. …”
    Get full text
    Get full text
    Get full text
    Proceeding Paper
  14. 14

    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. …”
    Get full text
    Get full text
    Get full text
    Article
  15. 15
  16. 16

    Phishing image spam classification research trends: Survey and open issues by John Abari, Ovye, Mohd Sani, Nor Fazlida, Khalid, Fatimah, Mohd Yunus Bin Sharum, Mohd Yunus, Mohd Ariffin, Noor Afiza

    Published 2020
    “…Furthermore, several public data sets, features set, classification methods, and measuring metrics are found and the popular once were pinpointed. …”
    Get full text
    Get full text
    Article
  17. 17

    Dynamic android malware category classification using semi-supervised deep learning by Mahdavifar, Samaneh, Kadir, Andi Fitriah Abdul, Fatemi, Rasool, Alhadidi, Dima, Ghorbani, Ali A

    Published 2020
    “…Despite the academic and industrial attempts, devising a robust and efficient solution for Android malware detection and category classification is still an open problem. Supervised machine learning has been used to solve this issue. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Proceeding Paper
  18. 18

    Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis by Rochin Demong, Nur Atiqah, Mohamed Razali, Murni Zarina, Kamaruddin, Juliana Noor, Shamsuddin, Sazwan, Awang, Nor Ain, Kamarudin, Norjuliatie, Wan Othman, Noor Faradilla

    Published 2025
    “…Furthermore, classification using the Random Forest algorithm depicted that a 95.3% accuracy (k=0.768), confirming robust predictive capability in identifying course approval status and demand trends. …”
    Get full text
    Get full text
    Get full text
    Article
  19. 19
  20. 20

    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.…”
    Get full text
    Get full text
    Get full text
    Article