Search Results - (( _ evaluation index algorithm ) OR ( image classification based algorithm ))

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  1. 1

    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

    Published 2015
    “…The results are evaluated by receiver operating characteristic (ROC) graph and the existing technique that gives the best performance is landscape expansion index. …”
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    Thesis
  2. 2

    Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

    Published 2021
    “…Finally, the effectiveness of the algorithm is evaluated based on the accuracy performance. …”
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    Article
  3. 3

    Lung cancer medical images classification using hybrid CNN-SVM by Abdulrazak Yahya, Saleh, Chee, Ka Chin, Vanessa, Penshie, Hamada Rasheed Hassan, Al-Absi

    Published 2021
    “…This paper presents an image classification method based on the hybrid Convolutional Neural Network (CNN) algorithm and Support Vector Machine (SVM). …”
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    Novel techniques for enhancement and segmentation of acne vulgaris lesions by Malik, A. S., Humayun, J., Kamel, N., Yap, F. B.-B.

    Published 2013
    “…Methods: For the first objective, an algorithm is developed based on the theory of high dynamic range (HDR) images. …”
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    Citation Index Journal
  6. 6

    Ripeness level classification for pineapple using RGB and HSI colour maps by Abu Bakar, Badrul Hisham, Ishak, Asnor Juraiza, Shamsuddin, Rosnah, Wan Hassan, Wan Zuha

    Published 2013
    “…An algorithm is developed using MATLAB software to evaluate features based on an image of the pineapple. …”
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    Article
  7. 7

    Monitoring the impacts of drought on land use/cover: a developed object-based algorithm for NOAA AVHRR time series data by Mokhtari, Ahmad, Mansor, Shattri, Mahmud, Ahmad Rodzi, Mohd Shafri, Helmi Zulhaidi

    Published 2011
    “…As a novel idea in this study, it developed a new object-based classification algorithm for AVHRR (Advanced Very High Resolution Radiometer) data. …”
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    Article
  8. 8

    Automated Segmentation And Classification Technique For Brain Stroke by Mohd Saad, Norhashimah, Abdullah, Abdul Rahim, Mohd Noor, Niza Suzaini, Mohd Ali, Nursabillilah

    Published 2019
    “…The algorithm performance has been evaluated using Jaccard Index, Dice Coefficient (DC) and both false positive rate (FPR) and false negative rate (FNR). …”
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    Article
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    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
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    Raspberry Pi-Based Finger Vein Recognition System Using PCANet by Quek, Ee Wen

    Published 2018
    “…For identification, the image processing involves process of image pre-processing, feature extraction and classification. …”
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    Monograph
  14. 14

    Artificial intelligence system for pineapple variety classification and its quality evaluation during storage using infrared thermal imaging by Mohd Ali, Maimunah

    Published 2022
    “…Multimodal data fusion based on three different CNN architectures including ResNet, VGG16, and InceptionV3 was designed for the classification of pineapple varieties with classification rate up to 92 %. …”
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    Thesis
  15. 15

    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. …”
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    Article
  16. 16

    Grain recognition based on colour and shape analysis by Mustaffa, Mas Rina, Nachiappan, Indra Nachammai, Abdullah, Lili Nurliyana, Khalid, Fatimah, Hussin, Masnida

    Published 2020
    “…This work aims to contribute to an automatic grain recognition using an image-based query instead of a text-based query. …”
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    Article
  17. 17

    Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification by Petwan, Montha

    Published 2023
    “…The performance of FESSIC was evaluated against ten benchmark image classification algorithms and six classifiers on four ground-based sky image datasets. …”
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    Thesis
  18. 18

    Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza by Khaimuza, Haris Hidayatullah

    Published 2024
    “…Second objective is to develop the prototype of daisy species classification based on image using CNN algorithm. The last objective is to evaluate the accuracy of CNN model in the daisy species classification based on image. …”
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    Thesis
  19. 19

    Comparison of Landsat 8, Sentinel-2 and spectral indices combinations for Google Earth Engine-based land use mapping in the Johor River Basin, Malaysia by Ju, Zeng, Tan, Mou Leong, Narimah Samat, Chang, Chun Kiat

    Published 2021
    “…This study aims to improve the land use mapping in a tropical region based on the GEE platform. Seven satellite images and indices combinations include Landsat 8 (C1), Sentinel-2 (C2), Landsat 8+Sentinel-2 (C3), Landsat 8+Indices (C4), Sentinel-2+Indices (C5), Landsat 8+Sentinel-2+Indices (C6), Normalized Difference Vegetation Index (NDVI)+Normalized Difference Water Index (NDWI)+Enhanced Vegetation Index (EVI)+Elevation (C7) were developed to evaluate the best combination for land use mapping in the Johor River Basin (JRB), Malaysia. …”
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    Article
  20. 20

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…In addition, the best band selected for image classification is not necessarily the best for classification.A Best Band Selection Index (BBSI) algorithm was developed which is capable of selecting the best band combination for image visualization and supervised classification. …”
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    Thesis