Search Results - adaptive k different extraction algorithm

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  1. 1

    Acoustic echo cancellation using adaptive filtering algorithms for quranic accents (Qiraat) identification by Kamarudin, Noraziahtulhidayu, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Abushariah, Mohammad A. M., Hashim, Shaiful Jahari, Hassan Azhari, Abd Rauf

    Published 2015
    “…In order to conduct the AEC, three adaptive algorithms known as affine projection (AP), least mean square (LMS), and recursive least squares (RLS) are used during the preprocessing phase. …”
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  2. 2

    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

    Published 2021
    “…K-Means algorithm a popular efficient clustering techniques and genetic algorithm a widely used evolutionary algorithm and known for its adaptive nature were combined to determine the level of handwriting legibility for each child. …”
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    Thesis
  3. 3

    Acoustic echo cancellation using adaptive filter for Quranic accent signals by Kamarudin, Noraziahtulhidayu, Al Haddad, Syed Abdul Rahman, Basiron, Azli, Hassan Azhari, Rauf

    Published 2024
    “…AP indicates 93.9% for all of the classification algorithm in used, while for LMS and RLS the results are differed varies on different pattern classification algorithm stated whereby with LMS and PPCA classification, 96.9 % for accuracy and 84.8% accuracy for LMS and KNN. …”
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    EEG-based emotion recognition using machine learning algorithms by Lam, Yee Wei

    Published 2024
    “…Throughout this research study, models like Support Vector Machine (SVM), K-Nearest Neighbours (KNN) and Adaptive Boosting (AdaBoost) will be explored. …”
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  6. 6

    Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment by Sojodishijani, Omid

    Published 2011
    “…Consequently, the proposed adaptive feature extraction technique and neighborhood-based classifier family are tightly integrated in an adaptive K-nearest neighbor classifier.…”
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    COMPUTER AIDED SYSTEM FOR BREAST CANCER DIAGNOSIS USING CURVELET TRANSFORM by MOHAMED ELTOUKHY, MOHAMED MESELHY

    Published 2011
    “…We started this study by developing a diagnosis system. Five feature extraction methods were developed with curvelet and wavelet coefficients to differentiate between different breast cancer classes. …”
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    Thesis
  9. 9

    Adaptive resonance theory-based hand movement classification for myoelectric control system by Fariman, Hessam Jahani

    Published 2014
    “…Five distinct hand movements are classified with an Adaptive Resonance Theory (ART) based neural network implemented, as it uses a combination of features extracted from four EMG signals. …”
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    Thesis
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    Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation by Chen, Qipeng, Xiong, Qiaoqiao, Huang, Haisong, Tang, Saihong, Liu, Zhenghong

    Published 2024
    “…Firstly, data augmentation is employed in the preprocessing stage to increase the diversity of training samples, thereby improving the model’s robustness and generalization capability. The K-means++ clustering algorithm generates candidate bounding boxes, adapting to defects of different sizes and selecting finer features earlier. …”
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  12. 12

    Development of a phantom and metal artifact correction (MAC) algorithm for post-operative spine computed tomography (CT) imaging / Noor Diyana Osman by Osman, Noor Diyana

    Published 2014
    “…The missing projection data due to metal region is detected and extracted using an improved technique of dual-step adaptive thresholding. …”
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    Thesis
  13. 13

    Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study by Wenjun, Ji, Adamchuk, Viacheslav I., Song, Chao Chen, Mat Su, Ahmad S., Ismail, Ashraf, Qianjun, Gan, Zhou, Shi, Biswas, Asim

    Published 2019
    “…In this field, it was not possible to predict extractable P and K using all tested sensor combinations or algorithms. …”
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  14. 14

    A novel AI-driven EEG images emotion recognition generalized classification model for cross-subject analysis by Li, Jingjing, Lee, Ching Hung, Duan, Dingna, Zhou, Yanhong, Xie, Xueguang, Wan, Xianglong, Liu, Tiange, Li, Danyang, Yu, Hao, Hasan, W. Z.W., Song, Haiqing, Wen, Dong

    Published 2025
    “…The SCTMSA model includes three primary components: (1) A Siamese subnet with a shared convolutional structure for extracting similarity features. (2) A transformer module with dual-head self-attention to capture global dependencies. (3) Based on traditional hard-assignment k-means clustering, we introduce a learnable soft-assignment mechanism and dynamic centroid updating strategy to achieve adaptive low-dimensional compression of the feature space. …”
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