Search Results - (( lesion classification using algorithm ) OR ( using function method algorithm ))

Search alternatives:

Refine Results
  1. 1
    Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC)

    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
    “…Results showed that the Leaf Lesion Classification (LLC) algorithm based on Artificial Bee colony (ABC) produced an average 96.83% of accuracy and average 1.66 milliseconds of processing time, indicating that LLC algorithm is better than algorithm such as Otsu, Canny, Roberts and Sobel. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  2. 2
    Automated feature extraction on brain MRI images for predicting multiple sclerosis patient disability

    Automated feature extraction on brain MRI images for predicting multiple sclerosis patient disability by M. Muslim, Ali

    Published 2022
    “…The first phase aims to investigate the best types of required data, features and algorithms to be used in the final proposed methodology to predict exact EDSS, and different ranges of EDSS. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  3. 3
    Novel techniques for enhancement and segmentation of acne vulgaris lesions

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

    Published 2013
    “…Conclusion: This article specifically discusses the contrast enhancement and segmentation for automated diagnosis system of acne vulgaris lesions. The results are promising that can be used for further classification of acne vulgaris lesions for final grading of the lesions.…”
    Get full text
    Get full text
    Get full text
    Citation Index Journal
    Save to List
    Saved in:
  4. 4
    STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION

    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
    “…A boost ensemble learning algorithm using Support Vector Machines (SVM) as initial classifiers and Artificial Neural Networks (ANN) as a final classifier is employed to learn the patterns of different skin lesion class features. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  5. 5
    Automated Segmentation And Classification Technique For Brain Stroke

    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). …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  6. 6
    A Novel Algorithm for Breast Lesion Detection Using Textons and Local Configuration Pattern Features With Ultrasound Imagery

    A Novel Algorithm for Breast Lesion Detection Using Textons and Local Configuration Pattern Features With Ultrasound Imagery by Acharya, U. Rajendra, Meiburger, Kristen M., Wei Koh, Joel En, Ciaccio, Edward J., Arunkumar, N., See, Mee Hoong, Mohd Taib, Nur Aishah, Vijayananthan, Anushya, Rahmat, Kartini, Fadzli, Farhana, Leong, Sook Sam, Westerhout, Caroline Judy, Chantre-Astaiza, Angela, Ramirez-Gonzalez, Gustavo

    Published 2019
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images

    Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images by Adil Humayun, Khan

    Published 2024
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  8. 8
    Automated diagnosis of focal liver lesions using bidirectional empirical mode decomposition features

    Automated diagnosis of focal liver lesions using bidirectional empirical mode decomposition features by Acharya, U. Rajendra, Koh, Joel En Wei, Hagiwara, Yuki, Tan, Jen Hong, Gertych, Arkadiusz, Vijayananthan, Anushya, Yaakup, Nur Adura, Abdullah, Basri Johan Jeet, Mohd Fabell, Mohd Kamil, Yeong, Chai Hong

    Published 2018
    “…After which, the extracted features were subjected to particle swarm optimization (PSO) technique for the selection of a set of optimized features for classification. Our automated CAD system can differentiate normal, malignant, and benign liver lesions using machine learning algorithms. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  9. 9
    Ensemble learning of deep learning and traditional machine learning approaches for skin lesion segmentation and classification

    Ensemble learning of deep learning and traditional machine learning approaches for skin lesion segmentation and classification by Adil H., Khan, Dayang Nurfatimah, Awang Iskandar, Jawad F., Al-Asad, Hiren, Mewada, Muhammad Abid, Sherazi

    Published 2022
    “…After that segmented region is classified into three types of skin lesion using hybrid features of Alex-Net and VGG-16 through the transfer learning approach. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  10. 10
    Identifying melanoma characteristics using directional imaging algorithm and convolutional neural network on dermoscopic images / Mohammad Asaduzzaman Rasel

    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. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  11. 11
    Feature selection and classification of ulcerated lesions using statistical analysis for WCE images

    Feature selection and classification of ulcerated lesions using statistical analysis for WCE images by Suman, S., Hussin, F.A., Malik, A.S., Ho, S.H., Hilmi, I., Leow, A.H.-R., Goh, K.-L.

    Published 2017
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  12. 12
    Digital segmentation of skin diseases / Hadzli Hashim and Razali Abdul Hadi

    Digital segmentation of skin diseases / Hadzli Hashim and Razali Abdul Hadi by Hashim, Hadzli, Abdul Hadi, Razali

    Published 2004
    “…RGB colour variegations are useful features used by the domain's experts in their morphological learning method for skin disease classification. …”
    Get full text
    Get full text
    Research Reports
    Save to List
    Saved in:
  13. 13
    An efficient AdaBoost algorithm for enhancing skin cancer detection and classification

    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. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  14. 14
    Automated Detection and Classification of Retinal Vein Occlusion Using Ultra-widefield Retinal Fundus Images and Transfer Learning

    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
    Save to List
    Saved in:
  15. 15
    Development of a CAD system for stroke diagnosis using machine learning on DWI-MRI images

    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). …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  16. 16
    Finding the root of nonlinear function using five bracketing method / Nur Afiqah Mohamed Azhar

    Finding the root of nonlinear function using five bracketing method / Nur Afiqah Mohamed Azhar by Mohamed Azhar, Nur Afiqah

    Published 2019
    “…Therefore, numerical method in the form of bracketing method is often used to find only the approximate root of the function. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  17. 17
    The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer

    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. We also explored five fields of dermatology using deep learning applications: (1) the classification of diseases by clinical photos, (2) der moto pathology visual classification of cancer, and (3) the measurement of skin diseases by smartphone applications and personal tracking systems. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  18. 18
    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions

    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…The second technique is to solve bi-objective functions by using the BOBAT algorithm. The third technique is an integration of BOGSA with BOBAT to produce a BOGSBAT algorithm. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  19. 19
    Determining the preprocessing clustering algorithm in radial basis function neural network

    Determining the preprocessing clustering algorithm in radial basis function neural network by S.L. Ang, H.C. Ong, H.C. Law

    Published 2008
    “…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  20. 20
    Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller

    Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller by Ismail, H. Muh Yusuf

    Published 2010
    “…Thus it is important to select the accurate membership functions but these methods possess one common weakness where conventional FLC use membership function and control rules generated by human operator. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:

Search Tools: