The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. Next, we examine the statistical effect of correlated prediction error and propose a method for Generalized Least Squares (GLS) on graphs. …”

Calculation algorithm implementing the proposed model. by Landry Djopkop Kouanang (17131748)

Calculation algorithm implementing the proposed model. by Landry Djopkop Kouanang (17131748)

Improve algorithm process. by Ziwei Wu (11386352)

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Algorithm process. by Wei Cui (92129)

“…This paper aims to address these challenges by proposing an automated DDoS attack detection algorithm using the Informer model. We introduce a windowing technique to segment network traffic into manageable samples, which are then input into the Informer for feature extraction and classification. …”

Optimization process of BO algorithm. by Hoa Thi Trinh (20347834)

“…Bayesian optimization (BO) algorithms, including BO—Gaussian Process, BO—Random Forest, and Random Search methods, were used to refine the XGBoost model architecture. …”

Improve algorithm settings. by Hui Zhao (7395)

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BM3D algorithmic process. by Xiyu Zheng (21703063)

“…To enhance image clarity, we applied noise reduction using the BM3D algorithm. We employed an improved UNet network model that incorporates SimAM and PSA modules, forming three attention mechanisms: TandemAT-UNet, ParallelAT-UNet, and NestedAT-UNet. …”

Processed results from ECG data with the P-T algorithm. by Daehyun Kwon (11985629)

“…Reverse polar transformed spectrogram images such as (d) were used to train, validate, and test the deep CNN models in our study.…”

Detection maps obtained using different algorithms for the Cri dataset. by Ruhan A (12403982)

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Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…”

Comparison of PSNR values of different algorithms. by Xiaojun Wang (50332)

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Changes in FID values of different algorithms. by Xiaojun Wang (50332)

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Comparison of SSIM values of different algorithms. by Xiaojun Wang (50332)

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Changes in loss values for different algorithms. by Xiaojun Wang (50332)

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Hyperparameters of self-supervised learning algorithms used in Experiments 1–5. by Lalit Pandey (13195488)

Detection maps obtained using different algorithms for the AVIRIS-II dataset. by Ruhan A (12403982)

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Detection maps obtained using different algorithms for the Grand Isle dataset. by Ruhan A (12403982)

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Detection maps obtained using different algorithms for the AVIRIS-I dataset. by Ruhan A (12403982)

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Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

“…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…”