Search Results - (( java application rsa algorithm ) OR ( lesion classification based algorithm ))

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  1. 1

    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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    Final Year Project
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    Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC) by Ahmad, Faudziah, Ku-Mahamud, Ku Ruhana, Sainin, Mohd Shamrie, Airuddin, Ahmad

    Published 2015
    “…In this paper, an algorithm to classify leaf disease severity based on lesions is presented. …”
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    Article
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    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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    Conference or Workshop Item
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    Novel techniques for enhancement and segmentation of acne vulgaris lesions by Malik, A. S., Humayun, J., Kamel, N., Yap, F. B.-B.

    Published 2013
    “…The proposed algorithm is compared with two other methods. The proposed enhancement algorithm shows better result than both the other methods based on CIF and ICN. …”
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    Citation Index Journal
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    Automated Segmentation And Classification Technique For Brain Stroke by Mohd Saad, Norhashimah, Abdullah, Abdul Rahim, Mohd Noor, Niza Suzaini, Mohd Ali, Nursabillilah

    Published 2019
    “…This study proposes a segmentation and classification technique to detect brain stroke lesions based on diffusion-weighted imaging (DWI). …”
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    Article
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    Identifying melanoma characteristics using directional imaging algorithm and convolutional neural network on dermoscopic images / Mohammad Asaduzzaman Rasel by Mohammad Asaduzzaman , Rasel

    Published 2024
    “…This research is divided into two phases – 1) Feature Engineering phase explains skin conditions based on lesion segmentation and different dermoscopic feature extraction, while 2) Classification phase detects Melanoma. …”
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    Thesis
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    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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    Thesis
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    Development of a CAD system for stroke diagnosis using machine learning on DWI-MRI images by Mohd Saad, Norhashimah, Azman, Izzatul Husna, Abdullah, Abdul Rahim, Hamzah, Rostam Affendi, Muda, Ahmad Sobri, Yamba, Farzanah Atikah

    Published 2025
    “…A hybrid segmentation technique, fuzzy c-means with active contour (FCMAC), is proposed to enhance lesion localization accuracy. For classification, the system evaluates traditional machine learning algorithms like support vector machine (SVM) and k-nearest neighbor (KNN), alongside deep learning models such as convolutional neural network (CNN) and bilayered neural network (BNN). …”
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    Article
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    The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer by Tehseen Mazhar, Inayatul Haq, Allah Ditta, Syed Agha Hassnain Mohsan, Faisal Rehman, Imran Zafar, Jualang Azlan Gansau, Lucky Poh Wah Goh

    Published 2023
    “…This article describes the fundamentals of ML-based implementations, as well as future limits and concerns for the production of skin cancer detection and classification systems. …”
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    Article
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    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
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    TB-FusionNet: a multi-scale feature fusion algorithm with spatial and channel cross-attention for tuberculosis detection by Ding, Zeyu, Yaakob, Razali, Tieng Wei, Koh, Azman, Azreen, Mohd Rum, Siti Nurulain, Zakaria, Nor Fadhlina, Ahmad Nazri, Azree Shahril

    Published 2026
    “…To address the aforementioned issues, this study proposes TB-FusionNet, a multi-scale feature fusion algorithm based on channel and spatial cross-attention mechanisms, for tuberculosis classification. …”
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    Article
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    Automated feature extraction on brain MRI images for predicting multiple sclerosis patient disability by M. Muslim, Ali

    Published 2022
    “…From the large-scale features, a correlation analysis is performed to select the highly correlated features used for predicting patients’ disability. This was based on machine learning and regression algorithms at the first phase. …”
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    Thesis