Search Results - (( based segmentation using algorithm ) OR ( framework segmentation using algorithm ))

Refine Results
  1. 1

    Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

    Published 2018
    “…In the preprocessing stage, the On-Line Noise Filtering Algorithm for Trajectory Segmentation Based on Minimum Description Length concept (ONF_TRS) is proposed to achieve trajectory segmentation and remove noise points in real time with low computational cost. …”
    Get full text
    Get full text
    Thesis
  2. 2

    Disparity map algorithm using hierarchical of bitwise pixel differences and segment-tree from stereo image by Zainal Azali, Muhammad Nazmi

    Published 2024
    “…The adaptability of the algorithm is demonstrated through a 3D surface reconstruction using a final disparity map. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  3. 3

    A feature-based approach for segmenting faces by Zaqout, I., Zainuddin, R., Baba, S.

    Published 2004
    “…In this paper, we propose a feature-based algorithm for segmenting faces that is sufficiently generic and is also easily extensible to cope with more demanding variations of the imaging conditions. …”
    Get full text
    Get full text
    Article
  4. 4

    Stereo matching algorithm using census transform and segment tree for depth estimation by Hamzah, Rostam Affendi, Zainal Azali, Muhammad Nazmi, Mohd Noh, Zarina, Tengku Wook, Tg Mohd Faisal, Zainal Abidin, Izwan

    Published 2023
    “…The proposed algorithm in this article has four steps in total, which starts with the matching cost computation using census transform, cost aggregation utilizes segment-tree, optimization using winner-takes-all (WTA) strategy, and post-processing stage uses weighted median filter. …”
    Get full text
    Get full text
    Get full text
    Article
  5. 5

    A framework for white blood cell segmentation in microscopic blood images using digital image processing by Sadeghian, Farnoosh, Seman, Zainina, Ramli, Abdul Rahman, Abdul Kahar, Badrul Hisham, Saripan, M. Iqbal

    Published 2009
    “…The segmentation is conducted using a proposed segmentation framework that consists of an integration of several digital image processing algorithms. …”
    Get full text
    Get full text
    Get full text
    Article
  6. 6

    Embedded car plate image recognition system by Moo Wui Hung

    Published 2008
    “…Captured license plate is segmented into individual character by using histogram-based approach. …”
    Get full text
    Learning Object
  7. 7

    Automatic liver tumor segmentation on computed tomography for patient treatment planning and monitoring by Moghbel, Mehrdad, Mashohor, Syamsiah, Mahmud, Rozi, Saripan, M. Iqbal

    Published 2016
    “…The proposed segmentation evaluated on real-world clinical data from patients is based on a hybrid method integrating cuckoo optimization and fuzzy c-means algorithm with random walkers algorithm. …”
    Get full text
    Get full text
    Article
  8. 8

    Image segmentation method for boundary detection of breast thermography using random walkers by Moghbel, Mehrdad

    Published 2013
    “…The performance of the proposed method was evaluated by a board of three professional radiologists and the final decision was based on the majority agreement. The segmentation was based on constant parameters among all images used in the study; these standard segmentation parameters achieved acceptable results in most cases. …”
    Get full text
    Get full text
    Thesis
  9. 9

    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
    “…This study introduces a novel method based on Two-tier Semantic Segmentation (2TSS) framework explicitly aimed at enhancing hotspot detection in thermal images of PV modules. …”
    Get full text
    Get full text
    Get full text
    Article
  10. 10

    Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images by Singh, V., Elamvazuthi, I., Jeoti, V., George, J., Swain, A., Kumar, D.

    Published 2016
    “…Methods: The developed framework comprises of five computational steps to segment the ATFL ligament region. …”
    Get full text
    Get full text
    Article
  11. 11

    Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images by Singh, V., Elamvazuthi, I., Jeoti, V., George, J., Swain, A., Kumar, D.

    Published 2016
    “…Methods: The developed framework comprises of five computational steps to segment the ATFL ligament region. …”
    Get full text
    Get full text
    Article
  12. 12

    Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

    Published 2019
    “…The segmentation iris is transformed to rectangular shape using the Rubber Sheet method. …”
    Get full text
    Get full text
    Thesis
  13. 13

    A Reinforcement Learning Based Adaptive ROI Generation for Video Object Segmentation by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

    Published 2021
    “…The proposed method has been validated using four commonly used video entity segmentation datasets: SegTrack V2, DAVIS 2016, CdNet 2014, and the Youtube-Object dataset. …”
    Get full text
    Get full text
    Article
  14. 14

    A detailed description on unsupervised heterogeneous anomaly based intrusion detection framework by Udzir, Nur Izura, Hajamydeen, Asif Iqbal

    Published 2019
    “…To accomplish this, a current segment (clustering) has been used and a few new parts (filtering, aggregating and feature analysis) have been presented. …”
    Get full text
    Get full text
    Get full text
    Article
  15. 15

    Development of brain tumor segmentation of magnetic resonance imaging (MRI) using u-net deep learning by Jwaid W.M., Al-Hussein Z.S.M., Sabry A.H.

    Published 2023
    “…The developed U-Net architecture has been applied on the MRI scan brain tumor segmentation dataset in MICCAI BraTS 2017. The results using Matlab-based toolbox indicate that the proposed architecture has been successfully evaluated and experienced for MRI datasets of brain tumor segmentation including 336 images as training data and 125 images for validation. …”
    Article
  16. 16
  17. 17

    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. …”
    Get full text
    Get full text
    Get full text
    Article
  18. 18

    Deep learning-based item classification for retail automation by Ling, Ji Xiang

    Published 2025
    “…Real-time processing was achieved through the integration of object detection algorithms like YOLO and image segmentation techniques. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  19. 19

    Fast shot boundary detection based on separable moments and support vector machine by Idan, Zinah N., Abdulhussain, Sadiq H., Mahmmod, Basheera M., Al-Utaibi, Khaled A., Syed Abdul Rahman Al-, Syed Abdul Rahman Al-Hadad, Sait, Sadiq M.

    Published 2021
    “…Second, for each active area, the moments are computed using orthogonal polynomials. Then, an adaptive threshold and inequality criteria are used to eliminate most of the non-transition frames and preserve candidate segments. …”
    Get full text
    Get full text
    Get full text
    Article
  20. 20

    Optimising acoustic features for source mobile device identification using spectral analysis techniques / Mehdi Jahanirad by Mehdi , Jahanirad

    Published 2016
    “…Both models optimize acoustic features for source mobile device identification based on near-silent segments. The proposed feature sets along with selected feature extraction methods from the literature are analyzed and compared by using supervised learning techniques (i.e. support vector machines, nearest-neighbor, naïve Bayesian, neural network, logistic regression, and ensemble trees classifier), as well as unsupervised learning techniques (i.e. probabilistic-based and nearest-neighbor-based algorithms). …”
    Get full text
    Get full text
    Thesis