Search Results - (( java segmentation using algorithm ) OR ( learning segment reporting 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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    A Novel Hybrid Unet-RBF and CNN-RBF Algorithm for Autism Spectrum Disorder Classification by Lim, Huey Chern, Abdulrazak Yahya, Saleh

    Published 2024
    “…This article proposes a hybrid deep learning approach for ASD classification, merging U-net and Radial Basis Functions for medical image segmentation and integrating Convolutional Neural Network with RBF for ASD classification. …”
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    Deep learning convolutional neural network algorithms for the early detection and diagnosis of dental caries on periapical radiographs: a systematic review by Musri, Nabila, Christie, Brenda, Ichwan, Solachuddin Jauhari Arief, Cahyanto, Arief

    Published 2021
    “…Identifying caries with a deep convolutional neural network-based detector enables the operator to distinguish changes in the location and morphological features of dental caries lesions. Deep learning algorithms have broader and more profound layers and are continually being developed, remarkably enhancing their precision in detecting and segmenting objects. …”
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  10. 10

    Development of Hybrid Convolutional Neural Network and Radial Basis Function for Autism Spectrum Disorder Classification by Huey Chern, Lim

    Published 2024
    “…Hence, this study proposed hybrid deep learning algorithms for ASD classification. Two algorithms merged: U-net neural network and Radial Basis Function (RBF) for medical image segmentation. …”
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    Radiomics analysis and supervised machine learning model for classification of cervical cancer images using diffusion weighted imaging-MRI by Ramli, Zarina

    Published 2024
    “…The semi-automated active contour model (ACM) algorithm (average ICC = 0.952 ± 0.009, p > 0.05) was found to be more robust and reproducible than fully manual segmentation (average ICC = 0.897 ± 0.011, p > 0.05). …”
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  14. 14

    Retinal Fluids Segmentation Using Volumetric Deep Neural Networks on Optical Coherence Tomography Scans by Alsaih, K., Yusoff, M.Z., Tang, T.B., Faye, I., Meriaudeau, F.

    Published 2020
    “…In this study, we have used the RETOUCH challenge dataset to segment various retinal fluids. Human performance reported in the challenge scored 0.71 in the dice similarity coefficient (DSC) metric. …”
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  15. 15

    APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN by SARI, YUNITA SARI

    Published 2011
    “…For the third contribution, we have applied the Self-Training algorithm which is one of the semi-supervised machines learning technique. …”
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  16. 16

    Retinal Microvascular Feature Extraction Using Faster Region-based Convolutional Neural Network by Mohammed Enamul, Hoque

    Published 2021
    “…The supervised CNN methods employ different algorithms that iteratively learn from data for analyzing data and predicting outcomes. …”
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    Validation of deep convolutional neural network for age estimation in children using mandibular premolars on digital panoramic dental imaging / Norhasmira Mohammad by Mohammad, Norhasmira

    Published 2022
    “…The semi-automated dental staging system developed in this study is based on the Malay children’s population and uses a brain-inspired learning algorithm termed "deep learning". The methodology is comprised of four major steps: image preprocessing, which adheres to the inclusion criteria for panoramic dental radiographs, segmentation, and classification of mandibular premolars according to Demirjian's staging system using the Dynamic Programming-Active Contour (DP-AC) method and Deep Convolutional Neural Network (DCNN), respectively, and statistical analysis. …”
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    Thesis