Search Results - (( semantics segmentation learning algorithm ) OR ( java implementation models algorithm ))

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  1. 1

    A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

    Published 2021
    “…We propose a new reinforced active learning strategy based on a deep reinforcement learning algorithm. …”
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    Article
  2. 2

    A novel deep learning instance segmentation model for automated marine oil spill detection by Temitope Yekeen, S., Balogun, A.L., Wan Yusof, K.B.

    Published 2020
    “…The study concluded that the deep learning instance segmentation model performs better than conventional machine learning models and deep learning semantic segmentation models in detection and segmentation. …”
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    Article
  3. 3

    A novel deep learning instance segmentation model for automated marine oil spill detection by Temitope Yekeen, S., Balogun, A.L., Wan Yusof, K.B.

    Published 2020
    “…The study concluded that the deep learning instance segmentation model performs better than conventional machine learning models and deep learning semantic segmentation models in detection and segmentation. …”
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    Article
  4. 4

    2TSS: Two-tier semantic segmentation framework with enhancement for hotspot detection of solar photovoltaic thermal images by Nurul Huda, Ishak, Iza Sazanita, Isa, Muhammad Khusairi, Osman, Mohd Shawal, Jadin, Kamarulazhar, Daud, Mohd Zulhamdy, Ab Hamid

    Published 2025
    “…This research enhances comprehension of multi-tier segmentation architectures in deep learning, focusing on optimizing performance for solar energy systems through comparative analysis of semantic models. …”
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    Article
  5. 5

    Enhanced Deep Learning Framework for Fine-Grained Segmentation of Fashion and Apparel by Usmani, U.A., Happonen, A., Watada, J.

    Published 2022
    “…This work proposes a deep learning framework that can learn how to detect and segment clothing objects accurately. …”
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    Article
  6. 6

    Enhanced Reinforcement Learning Model for Extraction of Objects in Complex Imaging by Usmani, U.A., Roy, A., Watada, J., Jaafar, J., Aziz, I.A.

    Published 2022
    “…The visualization and classification of the area of interest in any picture is therefore an important function in order to segment the image. We examine a variety of image segmentation algorithms and give our reinforcement learning algorithm that uses Deep Convolutional Neural Networks for the detection of irregular objects, which has been tested on four datasets. …”
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    Article
  7. 7

    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING by SALLEH AL-HUMAIKANI, MOHAMMED ABDULQAWI

    Published 2021
    “…RSA is one of these encryption algorithms that have been implemented in security systems. …”
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    Thesis
  8. 8

    Automated visual defect detection using deep learning by Loh, Xiao

    Published 2022
    “…The main goal of this project is to study and develop various automated defect detection models by utilizing state-of-the-art deep learning segmentation algorithms, including U-Net, Double U-Net, SETR, TransU-Net, TransDAU-Net, CAM and SEAM to perform semantic segmentation in fully supervised and weakly supervised learning manners. …”
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    Final Year Project / Dissertation / Thesis
  9. 9

    Deep learning semantic segmentation for water level estimation using surveillance camera by Muhadi, Nur 'Atirah, Abdullah, Ahmad Fikri, Bejo, Siti Khairunniza, Mahadi @ Othman, Muhammad Razif, Mijic, Ana

    Published 2021
    “…This work presented two well-established deep learning algorithms, DeepLabv3+ and SegNet networks, and evaluated their performances using several evaluation metrics. …”
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    Article
  10. 10

    Deep learning-based water segmentation for autonomous surface vessel by Mohd Adam, Muhammad Ammar, Ibrahim, Ahmad Imran, Zainal Abidin, Zulkifli, Mohd Zaki, Hasan Firdaus

    Published 2020
    “…In this work, the deep learning models based on Convolutional Neural Network (CNN) to implement binary semantic segmentation is studied. …”
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    Proceeding Paper
  11. 11

    Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

    Published 2003
    “…The library is implemented by using Java cryptographic service provider framework that conforms to Java Cryptographic Architecture (JCA) and Java Cryptographic Extension (JCE). …”
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    Monograph
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    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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    Thesis
  14. 14

    Effective query structuring with ranking using named entity categories for XML retrieval by Roko, Abubakar

    Published 2016
    “…The method employs Semantic Tags Extraction (STSE) algorithm to extract semantic tags of an element and Element Enrichment (EERM) algorithm to enrich the elements. …”
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    Thesis
  15. 15

    Development of brain tumor segmentation of magnetic resonance imaging (MRI) using u-net deep learning by Jwaid W.M., Al-Hussein Z.S.M., Sabry A.H.

    Published 2023
    “…The study built and trained the 3D U-Net CNN including encoding/decoding relationship architecture to perform the brain tumor segmentation because it requires fewer training images and provides more precise segmentation. …”
    Article
  16. 16

    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

    Published 2013
    “…The performance of Java programming model and native programming model are compared with respect to the execution time for blood vessel detection. …”
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    Conference or Workshop Item
  17. 17

    A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

    Published 2014
    “…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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    Final Year Project
  18. 18

    Computer-assisted pterygium screening system: a review by Abdani, Siti Raihanah, Zulkifley, Mohd Asyraf, Shahrimin, Mohamad Ibrani, Zulkifley, Nuraisyah Hani

    Published 2022
    “…The deep learning networks have been successfully implemented for three major purposes, which are to classify an image regarding whether there is the presence of pterygium tissues or not, to localize the lesion tissues through object detection methodology, and to semantically segment the lesion tissues at the pixel level. …”
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    Article
  19. 19

    Review of CNN in aerial image processing by Liu, Xinni, Kamarul Hawari, Ghazali, Han, Fengrong, Izzeldin Ibrahim, Mohamed Abdelaziz

    Published 2023
    “…In recent years, deep learning algorithm has been used in many applications mainly in image processing of object detection and classification. …”
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    Article
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