Search Results - (( lesion classification model algorithm ) OR ( java data normalization algorithm ))

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  1. 1

    Novel techniques for enhancement and segmentation of acne vulgaris lesions by Malik, A. S., Humayun, J., Kamel, N., Yap, F. B.-B.

    Published 2013
    “…Objectives: There are two main objectives: (i) to develop an algorithm for the enhancement of various acne vulgaris lesions; and (ii) to develop a method for the segmentation of enhanced acne vulgaris lesions. …”
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  2. 2
  3. 3

    Identifying melanoma characteristics using directional imaging algorithm and convolutional neural network on dermoscopic images / Mohammad Asaduzzaman Rasel by Mohammad Asaduzzaman , Rasel

    Published 2024
    “…Multiple deep-learning models are proposed for segmentation. Several imaging, computer vision, and pattern recognition algorithms are employed to describe five dermoscopic features. …”
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  4. 4

    Automated Detection and Classification of Retinal Vein Occlusion Using Ultra-widefield Retinal Fundus Images and Transfer Learning by Ivy Ong Siaw Yin, Ong

    Published 2024
    “…The approach seeks to utilise knowledge from pretraining to enhance the performance of the segmentation model. The study also evaluates the classification model trained with lesion masks to classify images accurately into the respective categories. …”
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  5. 5

    DeepPulmoTB: a benchmark dataset for multi-task learning of tuberculosis lesions in lung computerized tomography (CT) by Tan, Zhuoyi, Madzin, Hizmawati, Norafida, Bahari, ChongShuang, Yang, Sun, Wei, Nie, Tianyu, Cai, Fengzhou

    Published 2024
    “…To demonstrate the advantages of DeepPulmoTB, we propose a novel multi-task learning model, DeepPulmoTBNet (DPTBNet), for the joint segmentation and classification of lesion tissues in CT images. …”
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    Article
  6. 6

    An efficient AdaBoost algorithm for enhancing skin cancer detection and classification by Gamil, Seham, Zeng, Feng, Alrifaey, Moath, Asim, Muhammad, Ahmad, Naveed

    Published 2024
    “…To improve accuracy, the AdaBoost algorithm is utilized, which amalgamates weak classification models into a robust classifier with high accuracy. …”
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    Article
  7. 7

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…Even a normal people using clustering to grouping their data. …”
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  8. 8

    SANAsms: Secure short messaging system for secure GSM mobile communication by Anuar, N.B., Azlan, I.M., Wahid, A.W.A., Zakaria, O.

    Published 2008
    “…The system is developed using Java 2 Micro Edition (J2ME) which is written in Java. …”
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  9. 9

    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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  10. 10

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. …”
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  11. 11

    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
  12. 12

    Challenges of hidden data in the unused area two within executable files by Naji, Ahmed Wathik, Zaidan, A.A., Zaidan, B.B.

    Published 2009
    “…The designed algorithms were intended to help in proposed system aim to hide and retract information (data file) with in unused area 2 of any execution file(exe.file). …”
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  13. 13

    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

    Published 2017
    “…Two sets of experimental data involving 20 diabetic patients and 20 healthy subjects were collected from CITO laboratory Semarang Central Java, Indonesia. …”
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    Thesis