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  1. 1
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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  2. 2
    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING

    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
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  3. 3
    An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe

    An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe by Yakub Kayode, Saheed, Kazeem Alagbe, Gbolagade

    Published 2017
    “…Java programming language is used to implement the algorithm. …”
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  4. 4
    Secure Image Steganography Using Encryption Algorithm

    Secure Image Steganography Using Encryption Algorithm by Siti Dhalila, Mohd Satar, Roslinda, Muda, Fatimah, Ghazali, Mustafa, Mamat, Nazirah, Abd Hamid, An, P.K

    Published 2016
    “…A system based on the proposed algorithm will be implemented using Java and it will be more secured due to double-layer of security mechanisms which are RSA and Diffie-Hellman.…”
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  5. 5
    Segmentation of pulmonary cavity in lung CT scan for tuberculosis disease

    Segmentation of pulmonary cavity in lung CT scan for tuberculosis disease by Tan, Zhuoyi, Madzin, Hizmawati, Khalid, Fatimah, Beng, Ng Seng

    Published 2024
    “…Then, based on this threshold, the lesion tissue within the bounding box is extracted and forms a mask that can be used for semantic segmentation tasks. Finally, we use the generated TB semantic segmentation mask to train Unet and Vnet models to verify the effectiveness of the algorithm. …”
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  6. 6
    A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging

    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
    “…Second, the datasets taken for the semantic segmentation task are not balanced since certain classes are present more than the others. …”
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  7. 7
    Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach

    Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach by Vadiveloo, Mogana

    Published 2020
    “…Region merging approach is used to reduce over segmented regions produced by region-based image segmentation algorithms. …”
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  8. 8
    2TSS: Two-tier semantic segmentation framework with enhancement for hotspot detection of solar photovoltaic thermal images

    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
    “…However, the semantic segmentation approach has limitations in terms of accuracy, particularly for hotspot thermal images. …”
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  9. 9
    Digitally signed electronic certificate for workshop / Azinuddin Baharum

    Digitally signed electronic certificate for workshop / Azinuddin Baharum by Baharum, Azinuddin

    Published 2017
    “…Digital Signature was encrypted by RSA Algorithm, a very powerful asymmetrical encryption. …”
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  10. 10
    An Optimized Semantic Segmentation Framework for Human Skin Detection

    An Optimized Semantic Segmentation Framework for Human Skin Detection by Huong, Audrey, Ngu, Xavier

    Published 2024
    “…The study incorporating optimization strategy in semantic segmentation is underexplored in dermatology. …”
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  11. 11
    Malaria parasites segmentation in red blood cells images using mean-shift and median-cut

    Malaria parasites segmentation in red blood cells images using mean-shift and median-cut by Tn. Muda, Tn. Zalizam, A Salam, Rosalina

    Published 2010
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  12. 12
    Modelling semantic context for novelty detection in wildlife scenes

    Modelling semantic context for novelty detection in wildlife scenes by Yong, SP, Deng, JD, Purvis, MP

    Published 2010
    “…Working with wildlife image data, the framework starts with image segmentation, followed by feature extraction and classification of the image blocks extracted from image segments. …”
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  13. 13
    Determination of the onset of ventricular tachycardia

    Determination of the onset of ventricular tachycardia by Mohd Afzan, Othman, Norlaili, Mat Safri, Sinan S., Mohammed Sheet

    Published 2012
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  14. 14
    A novel deep learning instance segmentation model for automated marine oil spill detection

    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
    “…So far, detection and discrimination of oil spill and look-alike are still limited to the use of traditional machine learning algorithms and semantic segmentation deep learning models with limited accuracy. …”
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  15. 15
    A novel deep learning instance segmentation model for automated marine oil spill detection

    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
    “…So far, detection and discrimination of oil spill and look-alike are still limited to the use of traditional machine learning algorithms and semantic segmentation deep learning models with limited accuracy. …”
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  16. 16
    Effective query structuring with ranking using named entity categories for XML retrieval

    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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  17. 17
    Enhanced Deep Learning Framework for Fine-Grained Segmentation of Fashion and Apparel

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

    Published 2022
    “…The low-level feature data are extracted by the feature extraction module using Mask Region Convolutional Neural Network (RCNN) segmentation branches and Inception V3 used to extract the high-level semantic data. …”
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  18. 18
    Deep learning semantic segmentation for water level estimation using surveillance camera

    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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  19. 19
    Enhanced Reinforcement Learning Model for Extraction of Objects in Complex Imaging

    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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  20. 20
    Word segmentation of output response for sign language devices

    Word segmentation of output response for sign language devices by Za'bah, Nor Farahidah, Muhammad Nazmi, Ahmad Amierul Asyraf, Azman, Amelia Wong

    Published 2020
    “…The proposed text segmentation method in this work is by using the dynamic programming and back-off algorithm, together with the probability score using word matching with an English language text corpus. …”
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