Search Results - (( basic evaluation tree algorithm ) OR ( using codification based algorithm ))

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    BMTutor research design: Malay sentence parse tree visualization by Muhamad Noor, Yusnita, Jamaludin, Zulikha

    Published 2014
    “…As a result of the lack of models and algorithms have been introduced in both parsers, the model and algorithm development phase is introduced in the design of BMTutor.Output from the development process shows that the prototype is able to provide sentence correction for all 15 invalid sentences and can produce parse tree visualizations for all 20 sentences used for prototype testing.…”
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    Conference or Workshop Item
  3. 3

    Image Based Oil Palm Tree Crowns Detection by Muhammad Afif Zakwan, Zaili

    Published 2020
    “…Image Based Oil Palm Tree Crowns Detection system is a basic system that enables the detection of oil palm tree crowns from red, green and blue (RGB) aerial images. …”
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    Final Year Project Report / IMRAD
  4. 4

    Reliability of bench-mark datasets for crowd analytic surveillance by Ameen, Mohamed Abul Hassan, Malik, Aamir Saeed, Nicolas, Walter, Faye , Ibrahima, Nordin, Nadira

    Published 2015
    “…The diverseness of these databases are assessed, with respect to the performance of the basic algorithms using qualitatively and quantitatively. …”
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  5. 5

    Reliability of bench-mark datasets for crowd analytic surveillance by Hassan, M.A., Malik, A.S., Nicolas, W., Faye, I., Nordin, N.

    Published 2015
    “…The diverseness of these databases are assessed, with respect to the performance of the basic algorithms using qualitatively and quantitatively. …”
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    Conference or Workshop Item
  6. 6

    Reliability of bench-mark datasets for crowd analytic surveillance by Hassan, M.A., Malik, A.S., Nicolas, W., Faye, I., Nordin, N.

    Published 2015
    “…The diverseness of these databases are assessed, with respect to the performance of the basic algorithms using qualitatively and quantitatively. …”
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    Conference or Workshop Item
  7. 7

    Extracting crown morphology with a low-cost mobile LiDAR scanning system in the natural environment by Wang, Kai, Zhou, Jun, Zhang, Wenhai, Zhang, Baohua

    Published 2021
    “…The algorithm defined in this study was evaluated with manual measurements as reference, and the morphological parameters of the canopy obtained using the LOAM and LeGO-LOAM algorithms as the basic framework were compared. …”
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    Article
  8. 8

    Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning by Solihin M.I., Yanto, Hayder G., Maarif H.A.-Q.

    Published 2024
    “…One of the prominent methods to improve machine learning accuracy is by using ensemble method which basically employs multiple base models. In this paper, the stacking ensemble method is used to increase the accuracy of the machine learning model for LSM where the base (first-level) learners use five ML algorithms namely decision tree (DT), k-nearest neighbor (KNN), AdaBoost, extreme gradient boosting (XGB) and random forest (RF). …”
    Conference Paper
  9. 9

    Automatic extraction of digital terrain model and Building Footprint from airborne LiDAR data using rule-based learning techniques by Jifroudi, Hamidreza Maskani

    Published 2021
    “…Therefore, in this research an algorithm has been created which can achieve the following goals. 1) To generate DTM only with LiDAR data without the need for layers and other information from the area 2) To create a building footprint from the LiDAR data by removing the tree cover effect 3) To create an automatic system that can perform the production process of DTM and footprint without the intervention of an expert. …”
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    Thesis
  10. 10

    Discriminative feature representation for Malay children’s speech recognition / Seyedmostafa Mirhassani by Mirhassani, Seyedmostafa

    Published 2015
    “…Three speech databases were used for the experiments including prolonged Malay vowels and Malay continuous speech database based on children’s speech and TIMIT database based on adult speeches. …”
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    Thesis
  11. 11

    Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza by Ghulam , Murtaza

    Published 2021
    “…The extracted features are evaluated through six machine learning (ML) classifiers namely softmax, k-nearest neighbor (kNN), support vector machine, linear discriminant analysis, decision tree, and naive Bayes. …”
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    Thesis