Search Results - (( parameter estimation using algorithm ) OR ( features extraction sensor algorithm ))

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  1. 1

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
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    Thesis
  2. 2

    Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti by Abd Mukti, Shahrul Nizan

    Published 2022
    “…The study set four main objectives to achieve its aim: (1) To analyse RGB and multispectral sensor calibration, (2) To evaluate the optimal flight parameters for pothole modelling production using RGB imagery, (3) To investigate various classifier algorithms and band combinations for pothole region areas using multispectral imagery and (4) To validate geometric information from the extracted pothole. …”
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  3. 3

    Classification of heart sound signals for the detection of heart diseases / N. Shamsuddin and M. N. Taib by Shamsuddin, N., Taib, M. N.

    Published 2012
    “…The obtained frequency pattern features were fed to the FFNN and trained using Resilient Backpropagation (RPROP) algorithm. …”
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    Article
  4. 4

    Square groove detection based on forstner with canny edge operator using laser vision sensor by Mohammed Naji, Osamah Abdullah Ahmed

    Published 2023
    “…This research addresses 1he feature extraction algorithm of 1he square weld groove to make weld seam recognition more accurate. …”
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  5. 5

    Feature extraction and supervised learning for volatile organic compounds gas recognition by Mohd Tombel, Nor Syahira, Mohd Zaki, Hasan Firdaus, Mohd Fadglullah, Hanna Farihin

    Published 2023
    “…This research project aims to investigate effective feature extraction techniques that can be employed as discriminative features for machine learning algorithms. …”
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    Article
  6. 6

    Wearable Sensor Feature Fusion for Human Activity Recognition (HAR) : A Proposed Classification Framework by Norfadzlan, Yusup, Adnan Shahid, Khan, Izzatul Nabila, Sarbini, Nurul Zawiyah, Mohamad

    Published 2022
    “…Due to the extensive feature engineering and human feature extraction required by traditional machine learning algorithms, they are time consuming to develop. …”
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    Proceeding
  7. 7

    Multi-sensor fusion based on multiple classifier systems for human activity identification by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Alo, Uzoma Rita, Al-garadi, Mohammed Ali

    Published 2019
    “…To provide compact feature vector representation, we studied hybrid bio-inspired evolutionary search algorithm and correlation-based feature selection method and evaluate their impact on extracted feature vectors from individual sensor modality. …”
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  8. 8
  9. 9

    Internet of Things (IoT) based activity recognition strategies in smart homes: a review by Babangida, Lawal, Perumal, Thinagaran, Mustapha, Norwati, Yaakob, Razali

    Published 2022
    “…This technique is challenged by the nature of IoT technology and perceived data, as well as by human differences, which necessitated additional processing tasks to select significant features for the learning algorithms. In this work, we focus our review on activity recognition implementation strategies by examining various sensors and sensing technologies used to collect useful data from IoT devices, reviewing preprocessing and feature extraction techniques, as well as classification algorithms used to recognize human activities in smart homes. …”
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    Article
  10. 10

    Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke by Henry Friday , Nweke

    Published 2019
    “…First, to investigate existing multi-sensor and automatic feature extraction methods for human activity detection and health monitoring using motion sensor. …”
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    Thesis
  11. 11

    The noise reduction algorithm for star detection by Razaman, Anis Hannani, Ahmad, Yasser Asrul, Gunawan, Teddy Surya, Khalifa, Othman Omran, Saidin, Norazlina

    Published 2025
    “…This improvement in denoising leads to more precise centroid extraction, contributing to more reliable star sensor performance for space navigation applications…”
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    Article
  12. 12

    Estimation in spot welding parameters using genetic algorithm by Lukman, Hafizi

    Published 2007
    “…By using Genetic algorithm (GA) the spot welding parameters can be estimated.…”
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    Thesis
  13. 13

    Designing an expressive virtual Kompang on mobile device with tri-axial accelerometer by Leng, Hoo Yong, Mohd Norowi, Noris, Jantan, Azrul Hazri

    Published 2018
    “…This paper is therefore implemented a simple extraction method by extracting percussive features from embedded sensors to map with the output sound with minimum delay. …”
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  14. 14

    Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer by Tuerxun, Adilijiang

    Published 2017
    “…The result illustrated that just one sensor features (sensor 4) are significantly enough to build a good, accurate classifier model that can predict, and classify the oil palm FFB ripeness, rather than the proposed 4 bands sensors with 32 feature attributes. …”
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  15. 15

    Sensors Fusion based Online Mapping and Features Extraction of Mobile Robot in the Road Following and Roundabout by Ali, Mohammed A. H., Musa, Mailah, Wan Azhar, Wan Yusoff, Zamzuri, Hamedon, Zulkifli, Md. Yusof, Anwar, P. P. Abdul Majeed

    Published 2016
    “…A road feature extraction based mapping system using a sensor fusion technique for mobile robot navigation in road environments is presented in this paper. …”
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    Conference or Workshop Item
  16. 16

    Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Al-Garadi, Mohammed Ali

    Published 2019
    “…These sensors are pre-processed and different feature sets such as time domain, frequency domain, wavelet transform are extracted and transform using machine learning algorithm for human activity classification and monitoring. …”
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    Article
  17. 17

    Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse) by Jia, Xing Yeoh, Chuii, Khim Chong, Mohd Saberi, Mohamad, Yee, Wen Choon, Lian, En Chai, Safaai, Deris, Zuwairie, Ibrahim

    Published 2015
    “…The results from this experiment show estimated optimal kinetic parameters values, shorter computation time, and better accuracy of simulated results compared with other estimation algorithms.…”
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  18. 18

    Comparison Of Ridge Filters Performance in Human Vein Extraction Using 850nm Near Infrared Led Illumination by Abu Bakar Abd Rahman, Abdullah Bade, Fuei, Pien Chee

    Published 2023
    “…This paper investigates the performance of the ridge filters algorithm for vein feature extraction by using the NIR imaging technique to visualise human vein vessels. …”
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    Proceedings
  19. 19

    Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model by Mohammed Adam, Kunna Azrag

    Published 2021
    “…However, the large-scale kinetic parameters estimation using optimization algorithms is still not applied to the main metabolic pathway of the E. coli model, and they’re a lack of accuracy result been reported for current parameters estimation using this approach. …”
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  20. 20

    Performance comparison of classification algorithms for EEG-based remote epileptic seizure detection in wireless sensor networks by Abualsaud, Khalid, Mahmuddin, Massudi, Saleh, Mohammad, Mohamed, Amr

    Published 2014
    “…Identification of epileptic seizure remotely by analyzing the electroencephalography (EEG) signal is very important for scalable sensor-based health systems.Classification is the most important technique for wide-ranging applications to categorize the items according to its features with respect to predefined set of classes.In this paper, we conduct a performance evaluation based on the noiseless and noisy EEG-based epileptic seizure data using various classification algorithms including BayesNet, DecisionTable, IBK, J48/C4.5, and VFI.The reconstructed and noisy EEG data are decomposed with discrete cosine transform into several sub-bands.In addition, some of statistical features are extracted from the wavelet coefficients to represent the whole EEG data inputs into the classifiers.Benchmark on widely used dataset is utilized for automatic epileptic seizure detection including both normal and epileptic EEG datasets.The classification accuracy results confirm that the selected classifiers have greater potentiality to identify the noisy epileptic disorders.…”
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    Conference or Workshop Item