S1 File - Enhanced audience sentiment analysis in IoT-integrated metaverse media communication by Hongtao Wang (570131)

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Hyperparameter and model configurations. by Hongtao Wang (570131)

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Performance in best and worst case scenarios. by Hongtao Wang (570131)

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Datasets and experimental settings. by Hongtao Wang (570131)

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Response time by scenario (ms). by Hongtao Wang (570131)

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Ablation study: Component contribution analysis. by Hongtao Wang (570131)

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Element model generation method with geometric distribution errors by Yiqi Liu (21357815)

“…The product surface geometric distribution error is directly attached to the element nodes of the product ideal element model using the error surface reconstruction method and the replacement algorithm of the element node vector height based on the product’s point cloud data. …”

Learning of the transformer layer. by Xueliang Guo (4797057)

“…To overcome these challenges, we introduce an advanced neuroimaging technology based on deep learning, the SWI-BITR-UNet model. …”

<b>Ensemble Optimized Deep Learning-Based Framework</b> by D. Mahesh (19730962)

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The algorithms and score criterion used in DBN hybrid structure learning. by Aslı Yaman (22567074)

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.…”

Confusion Matrix for Subspace algorithm (3000 Learning Cycles) providing insight into the performance evaluation of Subspace algorithm. by Sadia Nazim (21440115)

Clustering Ensemble Algorithm Based on Weighted Random Walk Co-association Matrix by wen sun (20719247)

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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Supplementary Material for: An Online Machine Learning Algorithm-Based Prognostic Predictive Model for Maintenance Hemodialysis Patients by figshare admin karger (2628495)

“…Six types of machine learning algorithms based predictive models were constructed for prognostic prediction. …”

<b>Research on Differential Genes in Rheumatoid Arthritis Synovium Based on Multiple Machine Learning Algorithms</b> by changsheng liao (18193081)

“…<p dir="ltr"><b>Research on Differential Genes in Rheumatoid Arthritis Synovium Based on Multiple Machine Learning Algorithms</b></p>…”

A parabolic relationship between prediction errors and learning rates obtained by a cubic learning algorithm. by Boluwatife Ikwunne (22238697)