Search Results - (( developing lesion classification algorithm ) OR ( java application optimisation algorithm ))

  • Showing 1 - 13 results of 13
Refine Results
  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. …”
    Get full text
    Get full text
    Get full text
    Citation Index Journal
  2. 2

    STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION by Adil H., Khan, Dayang Nurfatimah, Awang Iskandar, Jawad F., Al-Asad, SAMIR, EL-NAKLA, SADIQ A., ALHUWAIDI

    Published 2021
    “…In this paper, we proposed profound learning strategy to address three primary assignments developing in the zone of skin lesion picture preparation, i.e., dermoscopic highlight, extraction and detection. …”
    Get full text
    Get full text
    Get full text
    Article
  3. 3
  4. 4

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
    Get full text
    Get full text
    Get full text
    Article
  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
    “…Furthermore, to enhance the model's capacity to capture TB lesion features, we introduce an improved iterative optimization algorithm that refines feature maps by integrating probability maps obtained in previous iterations. …”
    Get full text
    Get full text
    Get full text
    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
    “…The novelty lies in the combination of these techniques to develop a robust and accurate system for skin cancer classification. …”
    Get full text
    Get full text
    Get full text
    Article
  7. 7
  8. 8

    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 study also evaluates the classification model trained with lesion masks to classify images accurately into the respective categories. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  9. 9
  10. 10
  11. 11

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

    Published 2022
    “…During the early stage of automated pterygium screening system development, conventional machine learning techniques such as support vector machines and artificial neural networks are the de facto algorithms to detect the presence of pterygium tissues. …”
    Get full text
    Get full text
    Article
  12. 12

    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
    Get full text
    Get full text
    Thesis
  13. 13

    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
    “…Machine learning (ML) can enhance a dermatologist’s work, from diagnosis to customized care. The development of ML algorithms in dermatology has been supported lately regarding links to digital data processing (e.g., electronic medical records, Image Archives, omics), quicker computing and cheaper data storage. …”
    Get full text
    Get full text
    Get full text
    Article