Search Results - (( java segmentation using algorithm ) OR ( quality perception process algorithm ))

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  1. 1

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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    Thesis
  2. 2

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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  3. 3
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    Towards a unified image quality assessment technique for cross-content image processing applications by Baqar, Mohtashim *

    Published 2024
    “…To make efficient multimedia processing systems, understanding human perception is crucial. …”
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    Image Fusion Methods and Applications: A Review by Anita, Chaudhary

    Published 2023
    “…In a variety of applications, various digital image fusion algorithms have been created. An image that includes more information for human visual perception and is more valuable for additional vision processing is the result of image fusion, which pulls information from many images of a given scenario. …”
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    Article
  9. 9

    Grammar-based prosody modification for explicit control Malay language storytelling speech synthesis / Muhammad Izzad Ramli by Ramli, Muhammad Izzad

    Published 2018
    “…Consequently, new rules and algorithm that is MustFront rule, limitation rule, and two-steps pitch contour algorithm are introduced to increase the synthesized speech quality. …”
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  10. 10

    Permutation entropy based full-reference image quality qssessment by Baqar, Mohtashim *, Lau, Sian Lun *, Mansoor Ebrahim

    Published 2019
    “…Therefore, an image quality assessment(IQA) framework should be highly accurate as well as computationally efficient; making it viable to be used with different image processing applications, especially, with real-time applications. …”
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  11. 11

    Application of artificial neural network in discriminating the agarwood oil quality using significant chemical compounds / Mohd Hezri Fazalul Rahiman … [et al.] by Rahiman, Mohd Hezri Fazalul, Ismail, Nurlaila, Taib, Mohd Nasir, Mohd Ali, Nor Azah, Tajuddin, Saiful Nizam

    Published 2014
    “…Therefore, as part of an on-going research in grading the agarwood oil quality, the application of ANN is proposed to analyse agarwood oil quality using its chemical profiles. …”
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  12. 12

    Intelligent road recognition system for automous vehicle by Soon, Adrian Bee Toing

    Published 2013
    “…The image features are extracted using simple image processing algorithms and are trained using artificial neural network (ANN). …”
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  13. 13

    PATCH-IQ: A Patch Based Learning Framework For Blind Image Quality Assessment by Abdul Manap, Redzuan, Ling, Shao, Frangi, Alejandro Federico

    Published 2017
    “…This enables PATCH-IQ to identify the distortion affecting the image, a property that can be useful for further local processing stages. PATCH-IQ is evaluated on the standard IQA databases, and the provided scores are highly correlated to human perception of image quality. …”
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    Article
  14. 14

    TV Ghost Cancellation System Using Switched Capacitor Circuits by Mahmoud, Seedahmed Sharif

    Published 1998
    “…The perceptibility of the ghost signal is strongly subj ective and is a function of picture content and quality. …”
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    A rule-based image segmentation method and neural network model for classifying fruit in natural environment / Hamirul'aini Hambali by Hambali, Hamirul'aini

    Published 2015
    “…This method adds separation and inverse processes to the algorithm in order to produce the best segmented images. …”
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    Thesis
  17. 17

    Classification of transient disturbance using Wavelet based support vector machine / Fahteem Hamamy Anuwar by Anuwar, Fahteem Hamamy

    Published 2012
    “…Deubechies 4 (db4) was selected as a mother wavelet for the entire process in order to extract the features for the input of classifier. …”
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