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  1. 1
    Scene classification for aerial images based on CNN using sparse coding technique

    Scene classification for aerial images based on CNN using sparse coding technique by Qayyum, A., Malik, A.S., Saad, N.M., Iqbal, M., Faris Abdullah, M., Rasheed, W., Rashid Abdullah, T.A., Bin Jafaar, M.Y.

    Published 2017
    “…Recent developments include several approaches and numerous algorithms address the task. This article proposes a convolutional neural network (CNN) approach that utilizes sparse coding for scene classification applicable for HRRS unmanned aerial vehicle (UAV) and satellite imagery. …”
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  2. 2
    Scene classification for aerial images based on CNN using sparse coding technique

    Scene classification for aerial images based on CNN using sparse coding technique by Qayyum A., Malik A.S., Saad N.M., Iqbal M., Faris Abdullah M., Rasheed W., Rashid Abdullah T.A., Bin Jafaar M.Y.

    Published 2023
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  3. 3
    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning

    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
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  4. 4
    A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping

    A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping by Ahmed Asal Kzar, Ahmed Asal Kzar, M Jafri, Mohd Zubir, Mutter, Kussay N., Anwar, Saumi Syahreza

    Published 2016
    “…The first group was used as source samples for supervisor classification via the MHNNA. …”
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  5. 5
    A multilayered convolutional sparse coding framework for modeling of pooling operation of convolution neural networks

    A multilayered convolutional sparse coding framework for modeling of pooling operation of convolution neural networks by , Abdul Wahid, Khan, Adnan Umar, , Mukhtarullah, Khan, Sheroz, Shah, Jawad

    Published 2019
    “…The multilayered version of CSC(ML-CSC) is shown to be connected to forward pass of CNNs and dictionary learning and sparse coding algorithms of this model are analyzed for solving classification and inverse problems in image processing. …”
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    Proceeding Paper
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  6. 6
    Using genetic algorithms to optimise land use suitability

    Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

    Published 2012
    “…The erosion potential categories determined that heavy and severe class covered 35% of the area. Land use/ Land Cover is obtained by satellite image processing that the overall kappa of the classification is 87.4% and the overall accuracy is 89.6%. …”
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  7. 7
    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms

    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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  8. 8
    Short term load forecasting using a hybrid neural network

    Short term load forecasting using a hybrid neural network by Yap K.S., Abidin I.Z., Lim C.P., Shah M.S.

    Published 2023
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    Conference paper
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  9. 9
    Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification

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

    Published 2023
    “…Therefore, an improved feature extraction and selection for sky image classification (FESSIC) algorithm is proposed. …”
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  10. 10
    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani

    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 urban growth images obtained are analysed to improve existing classification algorithms. …”
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  11. 11
    Daisy species classification based on image using Convolutional Neural Network algorithm / Haris Hidayatullah Khaimuza

    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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  12. 12
    Object-Oriented Programming semantics representation utilizing agents

    Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

    Published 2011
    “…Novices tend to refer to source codes examples and adapt the source codes to the problem given in their assignments. …”
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  13. 13
    Phylogenetic tree classification system using machine learning algorithm

    Phylogenetic tree classification system using machine learning algorithm by Tan, Jia Kae

    Published 2015
    “…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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    Final Year Project Report / IMRAD
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  14. 14
    Laser-induced backscattering imaging for classification of seeded and seedless watermelons

    Laser-induced backscattering imaging for classification of seeded and seedless watermelons by Mohd Ali, Maimunah, Hashim, Norhashila, Bejo, Siti Khairunniza, Shamsudin, Rosnah

    Published 2017
    “…The laser-induced backscattering imaging technique is potentially useful for classification of seeded and seedless watermelons.…”
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  15. 15
    Maldroid- attribute selection analysis for malware classification

    Maldroid- attribute selection analysis for malware classification by Rahiwan Nazar, Romli, Mohamad Fadli, Zolkipli, Mohd Zamri, Osman

    Published 2019
    “…Hence, the objective of this paper is to find the most effective and efficient attribute selection and classification algorithm in malware detection. Moreover, in order to get the best combination between attribute selection and classification algorithm, eight attributes selection and seven categories machine learning algorithm are applied in this study. …”
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  16. 16
    Automatic classification of medical x-ray images

    Automatic classification of medical x-ray images by Zare, M.R., Seng, W.C., Mueen, A.

    Published 2013
    “…Image representation is one of the major aspects of automatic classification algorithms. …”
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  17. 17
    Region-growing based segmentation and bag of features classification for breast ultrasound images

    Region-growing based segmentation and bag of features classification for breast ultrasound images by Lee, Lay Khoon

    Published 2017
    “…In the next stage, which is the segmentation stage, region growing algorithm is used to automatically detect tumors in ultrasound images. …”
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  18. 18
    The use of SOM for fingerprint classification

    The use of SOM for fingerprint classification by Turky A.M., Ahmad M.S.

    Published 2023
    “…This paper introduces an approach to fingerprint classification by using Self-Organizing Maps (SOM). In order to be able to deal with fingerprint images having distorted regions, the SOM learning and classification algorithms are modified. …”
    Conference paper
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  19. 19
    Image Processing Of Digital Mammograms For Breast Cancer Detection And Classification

    Image Processing Of Digital Mammograms For Breast Cancer Detection And Classification by Mohd Nizom, Ahmad Nabil

    Published 2018
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    Monograph
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  20. 20
    Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms

    Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

    Published 2024
    “…It involves identifying and isolating relevant information from the images that classification algorithms can use to distinguish between different fruit categories. …”
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