Search Results - (( image classification modelling algorithm ) OR ( data visualization using algorithm ))

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  1. 1

    An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

    Published 2020
    “…This demonstrate the intensity of the correlation between that aspect of data and a specific cluster. In the classic Bag of visual words model, the Fuzzy c-means algorithm is replaced with K-means and the accuracy of SIFT matching is increased. …”
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    Article
  2. 2

    Imaging spectroscopy and light detection and ranging data fusion for urban features extraction by Idrees, Mohammed, Mohd Shafri, Helmi Zulhaidi, Saeidi, Vahideh

    Published 2013
    “…Hue Saturation Intensity (HSI) fusion algorithm was used to fuse the imaging spectroscopy and DSM as well as imaging spectroscopy and filtered intensity. …”
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    Article
  3. 3

    The formulation of a transfer learning pipeline for the classification of the wafer defects by Lim, Shi Xuen

    Published 2023
    “…Automated processes have been used commonly in recent years, with the judgement done by using conventional image processing algorithm. …”
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    Thesis
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    Machine learning application for concrete surface defects automatic damage classification by Syahrul Fithry Senin, Khairullah Yusuf, Amer Yusuf, Rohamezan Rohim

    Published 2024
    “…This model is trained using 80% of the image data and tested using another 20% of the image data. …”
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    Article
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    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

    Published 2017
    “…General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). …”
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    Article
  8. 8

    A novel framework for potato leaf disease detection using an efficient deep learning model by Mahum, R., Munir, H., Mughal, Z.-U.-N., Awais, M., Sher Khan, F., Saqlain, M., Mahamad, S., Tlili, I.

    Published 2022
    “…Moreover, the usage of the reweighted cross-entropy loss function makes our proposed algorithm more robust as the training data is highly imbalanced. …”
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    Article
  9. 9

    A novel framework for potato leaf disease detection using an efficient deep learning model by Mahum, R., Munir, H., Mughal, Z.-U.-N., Awais, M., Sher Khan, F., Saqlain, M., Mahamad, S., Tlili, I.

    Published 2022
    “…Moreover, the usage of the reweighted cross-entropy loss function makes our proposed algorithm more robust as the training data is highly imbalanced. …”
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    Article
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    Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia by San, Limhwee

    Published 2006
    “…Average filtering was applied to the PM10 map to mininise the noise effect. The proposed algorithms were also validated using the multidate data. …”
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    Thesis
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    Identifying the mechanism to forecast the progression of Alzheimer’s disease from mild cognitive impairment using deep learning by Hiu, Theresa Wei Xin

    Published 2022
    “…This study also implemented a CNN algorithm based on 3D ResNet-18 model using weights from ImageNet for the classification task of CN vs AD and sMCI vs pMCI. …”
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    Final Year Project / Dissertation / Thesis
  14. 14

    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

    Published 2019
    “…Based on the final denoised images, the model has proven its reliability, in terms of both visual quality and quantitative evaluation. …”
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    Thesis
  15. 15

    Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri by Basri, Katrul Nadia

    Published 2023
    “…The accuracy of the CNN model is comparable with the accuracy of the previous work that utilizing CNN for the imaging data to detect caries (diagnostic tool).…”
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    Thesis
  16. 16

    Urban landcover features identification utilizing multiband combinations and multi-level image segmentation for objectbased classification / Nurhanisah Hashim by Hashim, Nurhanisah

    Published 2018
    “…By adopting object based approached instead of pixel based will avoid the 'salt and pepper' effect that will decrease the accuracy of land-cover classification. Using Worldview-2 multispectral satellite image as a primary data, together with ancillary data which include normalized Digital Surface Model (nDSM) derived from Light Detection and Ranging (LIDAR) data and indices layer, the image segmentation process utilizing multiresolution segmentation algorithm was conducted. …”
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    Thesis
  17. 17

    Fusion of airborne LiDAR with multispectral SPOT 5 image for enhancement of feature extraction using Dempster–Shafer theory by Saeidi, Vahideh, Pradhan, Biswajeet, Idrees, Mohammed Oludare, Abd Latif, Zulkiflee

    Published 2014
    “…Subsequently, the classification accuracy was assessed using an IKONOS image of the study area as ground truth data. …”
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    Article
  18. 18

    Automated pavement imaging program (APIP) for pavement cracks classification and quantification – a photogrammetric approach by Mustaffar, Mushairry, Puan, O. C., Ling, Tung Chai

    Published 2008
    “…This visual survey method is not only time consuming and costly but more importantly it compromises the safety of the field personnel. …”
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    Conference or Workshop Item
  19. 19

    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
  20. 20

    Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

    Published 2018
    “…Statistical parameters like average, variance and grey-level co-occurrence matrix (GLCM) was set as a structural feature which provides several statistics information about the texture of an image. In the next phase, the SVM classifier was trained to achieve the best classification using training data and test data integrated with selected features. …”
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    Thesis