Search Results - (( based applications sensor algorithm ) OR ( image classification process algorithm ))

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  1. 1
    Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images

    Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Ahmad, Noordin

    Published 2014
    “…The images were used to explore the combined performance of a data mining (DM) algorithm and object-based image analysis (OBIA). …”
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  2. 2
    AUTONOMOUS MOBILE ROBOT VISION BASED SYSTEM: HUMAN DETECTION BY COLOR

    AUTONOMOUS MOBILE ROBOT VISION BASED SYSTEM: HUMAN DETECTION BY COLOR by Mohd Shah, Hairol Nizam, Ab Rashid, Mohd Zamzuri, Mohd Sobran, Nur Maisarah

    Published 2013
    “…One of the unique advantages in this project, the detection of human by color only uses image processing that generated by the algorithms itself without additional sensor like sonar or IF sensor.…”
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  3. 3
    Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data

    Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

    Published 2016
    “…The developed DT algorithm was applied to object-based classifications in the first study area. …”
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  4. 4
    Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm

    Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm by Khan, Talha Ahmed, Shaikh, Faraz Ahmed, Khan, Sheroz, Abdul Kadir, Kushsairy, Mohd Su'ud, Mazliham, Shahid, Zeeshan, Yahya, Muhammad

    Published 2019
    “…The results include flood probabilities and prediction analysis using proposed algorithm.…”
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    Proceeding Paper
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  5. 5
    Human emotion classifications for automotive driver using skin conductance response signal

    Human emotion classifications for automotive driver using skin conductance response signal by Minhad, Khairun Nisa', Md. Ali, Sawal Hamid, Ooi, Jonathan Shi Khai, Ahmad, Siti Anom

    Published 2016
    “…The affective assessment classification rate obtained from SCR processing was more than 70% accuracy based on the off-line support vector machine classifier-processing algorithm. …”
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    Conference or Workshop Item
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  6. 6
    Spectral discrimination and index development of roofing materials and conditions using field spectroscopy and worldview-3 satellite image

    Spectral discrimination and index development of roofing materials and conditions using field spectroscopy and worldview-3 satellite image by Samsudin, Sarah Hanim

    Published 2016
    “…Three feature selection algorithms of Genetic Algorithm (GA), Support Vector Machine (SVM) and Random Forest (RF) were used to select the most significant wavelengths since the algorithms works well with large size of data and widely applied for feature selection of hyperspectral remote sensing data. …”
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    Thesis
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  7. 7
    Near-infrared technique for oil palm fruit grading system

    Near-infrared technique for oil palm fruit grading system by Saeed, Osama Mohamed Ben

    Published 2013
    “…The grading systems in general utilized improved engineering designs with image processing techniques to ensure the quality of the product.In this research, a hyperspectral oil palm grading system was built and an image processing techniques algorithm was developed based on the spectral reflectance of the external features of oil palm fresh fruit bunches (FFB). …”
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  8. 8
    Modified hybrid median filter for removal of low density random-valued impulse noise in images / Dr. Siti Noraini Sulaiman ... [et al.]

    Modified hybrid median filter for removal of low density random-valued impulse noise in images / Dr. Siti Noraini Sulaiman ... [et al.] by Sulaiman, Siti Noraini, Isa, Iza Sazanita, Hussain, Zakaria, Md Tahir, Nooritawati, Mat Isa, Nor Ashidi

    Published 2017
    “…Impulse Noise (IN) is one of the common noises which are prevalent in noisy communication channels, faulty pixel sensors and memory location. Its affect the accuracy of various image processing applications such as image segmentation, image restoration, image classification and image compression. …”
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    Research Reports
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  9. 9
    Camera geometry determination based on circular's shape for peg-in-hole task

    Camera geometry determination based on circular's shape for peg-in-hole task by Farah Adiba, Azman

    Published 2019
    “…The peg-in-hole task is widely used in manufacturing process by using vision system and sensors. However, it requires complex algorithm and high Degree of Freedom (DOF) mechanism with fine movement. …”
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  10. 10
    Vision-based autonomous robot body alignment for copper wire spool pick up

    Vision-based autonomous robot body alignment for copper wire spool pick up by Daud, Mohd Razali, Shalfarina, Shahriman, Mohd Faudzi, Ahmad Afif, Sulaiman, Mohd Herwan, Irawan, Addie, Musa, Zulkifli

    Published 2019
    “…The peg-in-hole task is widely used in manufacturing process by using vision system and sensors but costly and needs complex algorithm. …”
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    Research Report
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  11. 11
    Ganoderma boninense disease detection by Near-Infrared Spectroscopy Classification: a review

    Ganoderma boninense disease detection by Near-Infrared Spectroscopy Classification: a review by Mohd Hilmi Tan, Mas Ira Syafila, Jamlos, Mohd Faizal, Omar, Ahmad Fairuz, Dzaharudin, Fatimah, Chalermwisutkul, Suramate, Akkaraekthalin, Prayoot

    Published 2021
    “…This review describes past and future prospects of integrated research of near-infrared spectroscopy (NIRS), machine learning classification for predictive analytics and signal processing towards an early G. boninense detection system. …”
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  12. 12
    A Review on the Development of Indonesian Sign Language Recognition System

    A Review on the Development of Indonesian Sign Language Recognition System by Jasni, Mohamad Zain, Sutarman, na, Mazlina, Abdul Majid

    Published 2013
    “…In order to improve recognition accuracy, researchers use methods, such as the hidden Markov model, artificial neural networks and dynamic time warping. Effective algorithms for segmentation, matching the classification and pattern recognition have evolved. …”
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  13. 13
    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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  14. 14
    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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  15. 15
    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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  16. 16
    Image classification using two dimensional wavelet coefficients with parallel computing

    Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

    Published 2020
    “…This method is capable to shorten the process time of the computation-intensive program in this research to process the live images frame by frame, which received from a laptop webcam to achieve real-time video processing. …”
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    Final Year Project / Dissertation / Thesis
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  17. 17
    Classification of herbs plant diseases via hierarchical dynamic artificial neural network

    Classification of herbs plant diseases via hierarchical dynamic artificial neural network by Abdullah, Lili Nurliyana, Khalid, Fatimah, Borhan, N.M.

    Published 2010
    “…The image processing is divided into four stages: Image Pre-Processing to remove image noises (Fixed-Valued Impulse Noise, Random-Valued Impulse Noise and Gaussian Noise), Image Segmentation to identify regions in the image that were likely to qualify as diseased region, Image Feature Extraction and Selection to extract and select important image features and Image Classification to classify the image into different herbs diseases classes. …”
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  18. 18
    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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  19. 19
    Classification of Citrus (Rutaceae) by Using Image Processing

    Classification of Citrus (Rutaceae) by Using Image Processing by Najwa Bari'ah Mohd Tabri

    Published 2019
    “…This research will be conducted by using digital image processing approach based on the morphological features of leaf with the combination of gray level co-occurrence matrix (GLCM), Prewitt and Canny algorithm and training classification models by using support vector machine (SVM). …”
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    Undergraduate Final Project Report
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  20. 20
    Classification of herbs plant diseases via hierachical dynamic artificial neural network after image removal using kernel regression framework

    Classification of herbs plant diseases via hierachical dynamic artificial neural network after image removal using kernel regression framework by Abdullah, Lili Nurliyana, Khalid, Fatimah, Borhan, N.M.

    Published 2011
    “…The image processing is divided into four stages: Image Pre-Processing to remove image noises (Fixed-Valued Impulse Noise, Random-Valued Impulse Noise and Gaussian Noise), Image Segmentation to identify regions in the image that were likely to qualify as diseased region, Image Feature Extraction and Selection to extract and select important image features and Image Classification to classify the image into different herbs diseases classes. …”
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