Search Results - (( leaf classification problems algorithm ) OR ( java _ normalization algorithm ))

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  1. 1

    Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari by Sha’ari, Nor Silawati

    Published 2018
    “…NN such as Artificial Neural Network (ANN) and K-Nearest Neighbor (KNN) is trained in developing a classification system for agriculture purpose. ANN and KNN is applied to solve the problems in image analysis, pattern recognition and classification. …”
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    Student Project
  2. 2

    Leaf condition analysis using convolutional neural network and vision transformer by Yong, Wai Chun, Ng, Kok Why, Haw, Su Cheng, Naveen, Palanichamy, Ng, Seng Beng

    Published 2024
    “…As a result, although customers may receive an excellent interactive features programme, the backend algorithm is not optimized. This problem may discourage users from applying the program to solve plant disease problems. …”
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    Article
  3. 3

    Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

    Published 2018
    “…Besides using solely a single leaf organ to recognize plant species, numerous studies have employed DL methods to solve multi-organ plant classification problem. …”
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    Thesis
  4. 4

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

    Published 2016
    “…Beside that, classic bag of visual words algorithm (BoVW) is based on kmeans clustering and every SIFT feature belongs to one cluster and it leads to decreasing classification results. …”
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    Thesis
  5. 5

    An evaluation of feature selection methods on multi-class imbalance and high dimensionality shape-based leaf image features by Sainin, Mohd Shamrie, Alfred, Rayner, Ahmad, Faudziah, Lammasha, Mohamed A.M

    Published 2017
    “…Multi-class imbalance shape-based leaf image features requires feature subset that appropriately represent the leaf shape.Multi-class imbalance data is a type of data classification problem in which some data classes is highly underrepresented compared to others.This occurs when at least one data class is represented by just a few numbers of training samples known as the minority class compared to other classes that make up the majority class.To address this issue in shapebased leaf image feature extraction, this paper discusses the evaluation of several methods available in Weka and a wrapperbased genetic algorithm feature selection.…”
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    Article
  6. 6

    A direct ensemble classifier for learning imbalanced multiclass data by Samry @ Mohd Shamrie Sainin

    Published 2013
    “…In addition, the selected benchmark data, experiments and the results are useful for future research on the imbalanced multiclass classification problem. Furthermore, the DECIML framework was applied to the real world leaf classification problem based on the shape features. …”
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    Thesis
  7. 7

    Improving resource management with multi-instance broker scheduling algorithm in hierarchical grid computing by Yahaya, Bakri

    Published 2016
    “…The designed modules is in the form of algorithms, GridSim, Java Development Kits and Java Language used to support the design process whereas the Netbeans software serves as the platform to simulate the experiment so as to obtain the results. …”
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    Thesis
  8. 8

    SANAsms: Secure short messaging system for secure GSM mobile communication by Anuar, N.B., Azlan, I.M., Wahid, A.W.A., Zakaria, O.

    Published 2008
    “…The system is developed using Java 2 Micro Edition (J2ME) which is written in Java. …”
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    Conference or Workshop Item
  9. 9

    Introducing new statistical shape based and texture feature extraction methods in the plant species recognition system by Seyed Mohammad Hussein, Ahmad, Siti Anom, Hassan, Mohd Khair, Ishak, Asnor Juraiza

    Published 2013
    “…The results show the outperformance of the two proposed methods for image processing and optimized classifier for classification part. As the classification result, radial basis neural networks (RBFNN), feed forward neural networks (FFNN), neural networks using genetic algorithm (NNUGA) shows 100%, 93%, 97.3% of accuracy respectively . …”
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    Article
  10. 10

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…On the Construction phase, the development of the prototype has been started. All the algorithm for the engine has been developed by using Java script language. …”
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    Thesis
  11. 11
  12. 12

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. …”
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    Thesis
  13. 13

    A multi-filter feature selection in detecting distributed denial-of-service attack by Yon, Yi Jun, Leau, Yu-Beng, Suraya Alias, Park, Yong Jin

    Published 2019
    “…In addition, the proposed M2FS method is developed through WEKA API with Java Programming language using the IDE of Eclipse Java. …”
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    Conference or Workshop Item
  14. 14

    Challenges of hidden data in the unused area two within executable files by Naji, Ahmed Wathik, Zaidan, A.A., Zaidan, B.B.

    Published 2009
    “…Results: The programs were coded in Java computer language and implemented on Pentium PC. …”
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    Article
  15. 15

    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

    Published 2017
    “…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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    Thesis