Showing 1 - 17 results of 17 for search '(((( complement fusion algorithm ) OR ( elements b algorithm ))) OR ( neural coding algorithm ))', query time: 0.12s Refine Results
  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6

    Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information by M. Ghoniem, Rania

    Published 2019
    “…In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. To overcome issues of feature extraction and multi-modal fusion, hybrid fuzzy-evolutionary computation methodologies are employed to demonstrate ultra-strong capability of learning features and dimensionality reduction. …”
    Get full text
    Get full text
  7. 7
  8. 8
  9. 9
  10. 10
  11. 11
  12. 12
  13. 13

    Microwave brain imaging system to detect brain tumor using metamaterial loaded stacked antenna array by Amran Hossain (570706)

    Published 2022
    “…The antenna is comprised of metamaterial-loaded with three substrate layers, including two air gaps. One 1 × 4 MTM array element is used in the top layer and middle layer, and one 3 × 2 MTM array element is used in the bottom layer. …”
  14. 14
  15. 15

    Identification And Weather Sensitivity Of Physically Based Model Of Residential Air-Conditioners For Direct Load Control: A Case Study by El-Ferik, S

    Published 2020
    “…An online maximum likelihood based-identification algorithm is developed. The required hardware and system instrumentation are detailed. …”
    Get full text
    article
  16. 16

    Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

    Published 2024
    “…For tabular data, we also present the Auto-Inflater neural network, utilizing an exponential loss function for Autoencoders. …”
  17. 17

    Developing an online hate classifier for multiple social media platforms by Joni Salminen (7434770)

    Published 2020
    “…We then experiment with several classification algorithms (Logistic Regression, Naïve Bayes, Support Vector Machines, XGBoost, and Neural Networks) and feature representations (Bag-of-Words, TF-IDF, Word2Vec, BERT, and their combination). …”