Search alternatives:
feature optimization » resource optimization (Expand Search), feature elimination (Expand Search), structure optimization (Expand Search)
policy optimization » topology optimization (Expand Search), wolf optimization (Expand Search), process optimization (Expand Search)
time feature » wise feature (Expand Search), line feature (Expand Search), entire feature (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based policy » based policies (Expand Search)
binary time » binary image (Expand Search)
feature optimization » resource optimization (Expand Search), feature elimination (Expand Search), structure optimization (Expand Search)
policy optimization » topology optimization (Expand Search), wolf optimization (Expand Search), process optimization (Expand Search)
time feature » wise feature (Expand Search), line feature (Expand Search), entire feature (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based policy » based policies (Expand Search)
binary time » binary image (Expand Search)
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Sample image for illustration.
Published 2024“…We have developed two filters capable of computing pixel intensity variations, followed by the covariance matrix of the polynomial to describe the features. The superiority of CBFD is validated through precision, recall, computation time, and feature location distance. …”
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Process flow diagram of CBFD.
Published 2024“…We have developed two filters capable of computing pixel intensity variations, followed by the covariance matrix of the polynomial to describe the features. The superiority of CBFD is validated through precision, recall, computation time, and feature location distance. …”
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Precision recall curve.
Published 2024“…We have developed two filters capable of computing pixel intensity variations, followed by the covariance matrix of the polynomial to describe the features. The superiority of CBFD is validated through precision, recall, computation time, and feature location distance. …”
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Quadratic polynomial in 2D image plane.
Published 2024“…We have developed two filters capable of computing pixel intensity variations, followed by the covariance matrix of the polynomial to describe the features. The superiority of CBFD is validated through precision, recall, computation time, and feature location distance. …”
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90
Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP
Published 2022“…In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …”
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