Search Results - (( java application system algorithm ) OR ( sequence classification approach algorithm ))

Refine Results
  1. 1

    Optimized tree-classification algorithm for classification of protein sequences by Iqbal, M.J., Faye, I., Said, A.M., Belhaouari Samir, B.

    Published 2016
    “…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
    Get full text
    Get full text
    Conference or Workshop Item
  2. 2

    Optimized tree-classification algorithm for classification of protein sequences by Iqbal, M.J., Faye, I., Said, A.M., Belhaouari Samir, B.

    Published 2016
    “…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
    Get full text
    Get full text
    Conference or Workshop Item
  3. 3

    Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification by Nisar, Humaira, Malik, Aamir Saeed, Choi, Tae-Sun

    Published 2012
    “…This is the basis of the proposed algorithm. The proposed algorithm involves a multistage approach that includes motion vector prediction and motion classification using the characteristics of video sequences. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4

    Extraction and Optimization of Fuzzy Protein Sequences Classification Rules Using GRBF Neural Networks by Wang, Dianhui, Lee, Nung Kion, Dillon, Tharam S.

    Published 2003
    “…These feature patterns were originally extracted by sequence alignment algorithms, which measure similarity between an unseen protein sequence and identified protein sequences. …”
    Get full text
    Get full text
    Get full text
    Article
  5. 5

    Data Mining for Building Neural Protein Sequence Classification Systems with Improved Performance by Wang, Dianhui, Lee, Nung Kion, Dillon, Tharam S.

    Published 2003
    “…These feature patterns were originally extracted by sequence alignment algorithms, which measure similarity between an unseen protein sequence and identified protein sequences. …”
    Get full text
    Get full text
    Get full text
    Proceeding
  6. 6

    A Multi-tier Model and Filtering Approach to Detect Fake News Using Machine Learning Algorithms by Yu, Chiung Chang, A Hamid, Isredza Rahmi, Abdullah, Zubaile, Kipli, Kuryati, Amnur, Hidra

    Published 2024
    “…Many previous researchers have proposed this domain using classification algorithms or deep learning techniques. …”
    Get full text
    Get full text
    Article
  7. 7
  8. 8

    An improved particle swarm optimization algorithm for data classification by Waqas Haider Bangyal, Kashif Nisar, Tariq Rahim Soomro, Ag Asri Ag Ibrahim, Ghulam Ali Mallah, Nafees Ul Hassan, Najeeb Ur Rehman

    Published 2023
    “…Optimisation-based methods are enormously used in the field of data classification. Particle Swarm Optimization (PSO) is a metaheuristic algorithm based on swarm intelligence, widely used to solve global optimisation problems throughout the real world. …”
    Get full text
    Get full text
    Get full text
    Article
  9. 9
  10. 10
  11. 11

    Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga by Mwenge , Mulenga

    Published 2022
    “…Recent achievements in next generation sequencing technology that have resulted in an increased availability of sequence data have also created an enabling environment for the growth of the gut microbiome research area. …”
    Get full text
    Get full text
    Get full text
    Thesis
  12. 12
  13. 13

    Moment-based extraction on handwritten digits by Taliba, Jumail, Shamsuddin, Siti Mariyam, Tan, Shuen Chuan

    Published 2005
    “…These include geometric moments, Zernike moments and contour sequence moments. Classification and recognition results are analyzed to determine the necessity of operation thinning when dealing with the moment functions. …”
    Get full text
    Get full text
    Monograph
  14. 14

    Multitasking deep neural network models for Arabic dialect sentiment analysis by Alali, Muath Mohammad Oqlah

    Published 2022
    “…Most of the applied approaches are based on single task learning (STL) using machine learning algorithms, such as Logistic Regression (LR) and Hierarchical Classifier (HC) based on the divide-and-conquer approach. …”
    Get full text
    Get full text
    Thesis
  15. 15

    Real-time algorithmic music composition application. by Yap, Alisa Yi Hui

    Published 2022
    “…In addition, the system also utilises JavaFx and jFugue for its graphical user interface and music programming respectively. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  16. 16

    Convolutional neural networks with feature fusion method for automatic modulation classification by Elshebani, Mohamed Salem, Ali, Yahya, Azroug, Nser, Khalifa, Ramdan A. M., Khalifa, Othman Omran, Saeed, Rashid A.

    Published 2023
    “…However, most existing modulation classification algorithms are neglecting the fact of mixing features between different representations, and the importance of features fusion method. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceeding Paper
  17. 17

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
    Get full text
    Get full text
    Final Year Project
  18. 18

    A review on data stream classification by A. A, Haneen, A., Noraziah, Abd Wahab, Mohd Helmy

    Published 2018
    “…As such the typical tasks of searching data have been linked to streams of data that are inclusive of clustering, classification, and repeated mining of pattern. This paper presents several data stream clustering approaches, which are based on density, besides attempting to comprehend the function of the related algorithms; both semi-supervised and active learning, along with reviews of a number of recent studies.…”
    Get full text
    Get full text
    Get full text
    Article
  19. 19
  20. 20

    Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm by Ismail, Asmida, Ahmad, Siti Anom, Che Soh, Azura, Hassan, Mohd Khair, Harith, Hazreen Haizi

    Published 2020
    “…Experimental results show that there are reasonable and efficient to combine classic object detection method with a deep learning classification approach. The performance of this method can work in some specific use cases and effectively solving the problem of the inaccurate classification and detection of typical features.…”
    Get full text
    Get full text
    Get full text
    Article