Search Results - (( developing activation function algorithm ) OR ( based classification learning algorithm ))

Refine Results
  1. 1

    Jogging activity recognition using k-NN algorithm by Afifah Ismail

    Published 2022
    “…The objective of this project are 1) to investigate human activity recognition (HAR) for jogging activity and k-Nearest Neighbors (k-NN) algorithm for jogging classifier, 2) to apply HAR AND k-NN for jogging recognition and classification and, 3) to test the functionality of the k-NN algorithm of jogging recognition and classification. …”
    Get full text
    Get full text
    Get full text
    Academic Exercise
  2. 2

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
    Get full text
    Get full text
    Thesis
  3. 3

    Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

    Published 2008
    “…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
    Get full text
    Get full text
    Get full text
    Thesis
  4. 4

    Development of track-driven agriculture robot with terrain classification functionality / Khairul Azmi Mahadhir by Mahadhir, Khairul Azmi

    Published 2015
    “…In this work, an agricultural robot is embedded with machine learning algorithm based on Support Vector Machine (SVM). …”
    Get full text
    Get full text
    Thesis
  5. 5

    Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

    Published 2020
    “…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
    Get full text
    Get full text
    Thesis
  6. 6

    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

    Published 2004
    “…A novel feature extraction algorithm was developed to extract the feature vectors. …”
    Get full text
    Get full text
    Thesis
  7. 7

    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

    Published 2017
    “…MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. …”
    Get full text
    Get full text
    Article
  8. 8

    Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

    Published 2006
    “…Previously, there is limited work on the clustering and classification of biologically active compounds into their activity based classes using fuzzy and neural network. …”
    Get full text
    Get full text
    Monograph
  9. 9

    Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak by Abd Razak, Hana'

    Published 2020
    “…Towards achieving better detection in real-time environment, colour pixel-based images were trained on five pre-trained CNNs using transfer learning algorithm. …”
    Get full text
    Get full text
    Thesis
  10. 10
  11. 11

    Extreme Learning Machine neural networks for multi-agent system in power generation by Yaw C.T., Wong S.Y., Yap K.S., Tan C.H.

    Published 2023
    “…Extreme Learning Machine (ELM) is widely known as an effective learning algorithm than the conventional learning methods from the point of learning speed as well as generalization. …”
    Article
  12. 12

    Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification by Abdul Wahit, Mohamad Aizat

    Published 2019
    “…The tasks were performed without any failure and show the developed robot hand is reliable. Furthermore, the Support vector machine (SVM) and Linear discriminant analysis (LDA) machine learning for the hand posture classification based on the EMG signal pattern were investigated and compared in term of classification performance. …”
    Get full text
    Get full text
    Thesis
  13. 13

    Stress mental health symptom assessment mobile application for young adults by Lee, Chun Hoong

    Published 2023
    “…Moreover, users can provide more inputs based on their feelings throughout the day. One of the primary functionalities of the application is to incorporate a machine learning algorithm which is K-Nearest Neighbor (KNN) classification technique for panic attack prediction feature to enhance the emotional identification and offering users an artificial intelligence (AI) chatbot. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  14. 14

    Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification by Sobhan Sheykhivand, Tohid Yousefi Rezaii, Zohreh Mousavi, Azra Delpak, Ali Farzamnia

    Published 2020
    “…In this research, a fully automated system is presented to automatically detect the various states of the epileptic seizure. This study is based on sparse representation-based classification (SRC) theory and the proposed dictionary learning using electroencephalogram (EEG) signals. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  15. 15

    Electromygraphy (EMG) signal based hand gesture recognition using Artificial Neural Network (ANN) by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

    Published 2011
    “…Electromyography (EMG) signal is a measure of muscles' electrical activity and usually represented as a function of time, defined in terms of amplitude, frequency and phase. …”
    Get full text
    Get full text
    Get full text
    Proceeding Paper
  16. 16

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
    Get full text
    Get full text
    Thesis
  17. 17

    Modular deep neural network in reducing overfitting to enhance generalization / Mohd Razif Shamsuddin by Shamsuddin, Mohd Razif

    Published 2024
    “…It is found out that grayscale format works better as it retains the original information of the inputs and produced better precision based on the highest accuracy of 98.11%. Consecutively at the second phase, DNN models with different optimizers, batch size and activation functions are trained and analysed. …”
    Get full text
    Get full text
    Thesis
  18. 18

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
    Get full text
    Get full text
    Thesis
  19. 19

    Grid base classifier in comparison to nonparametric methods in multiclass classification by Moheb Pour, Majid Reza, Jantan, Adznan, Saripan, M. Iqbal

    Published 2010
    “…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
    Get full text
    Get full text
    Get full text
    Article
  20. 20

    Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Hence, this situation is believed in yielding of decreasing the classification accuracy. In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
    Get full text
    Get full text
    Get full text
    Article