Search Results - (( image classification success algorithm ) OR ( java application based algorithm ))

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  1. 1

    Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin by Nasaruddin, Nor Intan Shafini

    Published 2012
    “…The image classification prototype is developed by using JAVA programming language which is based on supervised learning algorithm, Backpropagation Neural Network. …”
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    Thesis
  2. 2

    An improved defect classification algorithm for six printing defects and its implementation on real printed circuit board images by Ibrahim, I., Ibrahim, Z., Khalil, K., Mokji, M.M., Abu Bakar, S.A.R.S., Mokhtar, N., Ahmad, W.K.W.

    Published 2012
    “…The improved PCB defect classification algorithm has been applied to real PCB images to successfully classify all of the defects. …”
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    Article
  3. 3

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…In general, image segmentation isolates an object from the images, feature extraction creates features for classification phase while object classification categorizes objects into the correct groups. …”
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    Thesis
  4. 4

    An Ar Natural Marker Similarities Measurement Algorithm For E-Biodiversity by Tan, Mei Synn, Wang, Yin Chai

    Published 2018
    “…The objective of this research is to comparatively evaluate the effectiveness of different algorithms, method combination procedure, and their parameters towards classification accuracy. …”
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    Proceeding
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    Classification of Planetary Nebulae through Deep Transfer Learning by Dayang N.F., Awang Iskandar, Zijlstra, Albert A., McDonald, Iain, Rosni, Abdullah, Fuller, Gary A., Ahmad H., Fauzi, Johari, Abdullah

    Published 2020
    “…We found that the algorithm has high success in distinguishing True PNe from other types of objects even without any parameter tuning. …”
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    Article
  8. 8

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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    Final Year Project
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    A Voting Technique Of Multilayer Perceptron Ensemble For Classification Application by Talib, Hafizah

    Published 2014
    “…In this research, an integrated system of Multi-Layer Perceptron Ensemble (MLPE) consisting of an MLPE and a new voting algorithm has been developed to increase classification accuracy and reduce the number of reject class cases. …”
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    Thesis
  11. 11

    An image segmentation algorithm for measurement of flotation froth bubble size distributions by Jahedsaravani, A., Massinaei, M., Marhaban, Mohammad Hamiruce

    Published 2017
    “…In this work a new watershed algorithm based on whole and sub-image classification techniques is introduced and successfully validated by several laboratory and industrial scale froth images taken under different process conditions. …”
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    Article
  12. 12

    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
  13. 13

    Image classification of Aedes mosquitoes using transfer learning / Zetty Ilham Abdullah by Abdullah, Zetty Ilham

    Published 2021
    “…In recent years, the importance, and uses of computer vision, notably image classification, to tackle real-world issues have grown. …”
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    Thesis
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    Optimized image enhancement of colour processing for retinal fundus image by Nurul Atikah, Mohd Sharif

    Published 2025
    “…It achieved a 95.034% success rate in classification accuracy. The study introduces a new colour correction model and an optimized image enhancement model, significantly improving retinal fundus image quality and establishing the most effective model for image quality enhancement…”
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    Thesis
  16. 16

    Optimized image enhancement of colour processing for retinal fundus image by Nurul Atikah, Mohd Sharif

    Published 2025
    “…It achieved a 95.034% success rate in classification accuracy. The study introduces a new colour correction model and an optimized image enhancement model, significantly improving retinal fundus image quality and establishing the most effective model for image quality enhancement…”
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    Thesis
  17. 17

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…In general, image segmentation isolates an object from the images, feature extraction creates features for classification phase while object classification categorizes objects into the correct groups……”
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    Book Section
  18. 18

    Development of interactive application for classification of Artocarpus Species by Abdul Ghapar, Nadia

    Published 2020
    “…Support Vector Machine (SVM) will be used to get the highest accuracy for the classification of Artocarpus species. The combination of Prewitt algorithm, Canny alogorithm, Gray-Level co-occurrence matrix will be used in SVM. …”
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    Undergraduate Final Project Report
  19. 19

    Classification of transient facial wrinkle by Rosdiyana, Samad, Mohammad Zarif, Rosli, Nor Rul Hasma, Abdullah, Mahfuzah, Mustafa, Dwi, Pebrianti, Nurul Hazlina, Noordin

    Published 2019
    “…Many researches have been done in the detection or classification of wrinkle, but it still needs some improvement in the algorithms, either in feature extraction part or classification. …”
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    Conference or Workshop Item
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    Bleeding classification of enhanced wireless capsule endoscopy images using deep convolutional neural network by Rosdiana, Shahril, Saito, Atsushi, Shimizu, Akinobu, Sabariah, Baharun

    Published 2020
    “…In this study, a pre-processing technique has been proposed to improve the classification accuracy of WCE images into bleeding areas and normal areas by enhancing the WCE images. …”
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    Article