Deep learning-based locomotive syndrome prediction method. by Junichi Kushioka (12236447)

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The most common machine learning methods to predict ν_s. by Fahd Saeed Alakbari (10701871)

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The optimized parameters of the proposed GPR method. by Fahd Saeed Alakbari (10701871)

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The refracted opposition-based learning mechanism. by Yang Guo (399435)

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Development of a machine learning method for predicting neutrophil-specific functional genes. by Guihua Wang (286390)

RMSE versus learning rate. by Zhe Hu (787283)

Comparison of the results of our model and other methods. by Weijia Zhu (65481)

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outcome of HPDL-MIAIHD technique with recent methods. by Naif Almakayeel (16846021)

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Learn!Bio study: Grouping of Participants. by Katy Andrews (22311170)

“…A total of 317 Bioscience undergraduate students in years 1–3 at the biology department at a northwest English university participated in this anonymous, cross-sectional, mixed-method study with open and closed questions evaluating their perception and feedback to remote and blended learning provisions during the Covid-19 pandemic and post pandemic learning capturing academic years 2019/20–2022/23. …”

CT outcome of HPDL-MIAIHD technique with other methods. by Naif Almakayeel (16846021)

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Comparison of our model with other state-of-the-art methods. by Weijia Zhu (65481)

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CT outcome of HPDL-MIAIHD technique with recent methods. by Naif Almakayeel (16846021)

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Evaluation of the effectiveness of double task. by Fan Yang (1413)

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Visualized results of different boundary labels. by Fan Yang (1413)

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Dice scores for each tissue type in the DUKE dataset, as well as the average Dice score and average IoU for each tissue type. by Fan Yang (1413)

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Predicted results of the TCCT [4] network. by Fan Yang (1413)

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Evaluation of the effectiveness of pruning. by Fan Yang (1413)

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Evaluation of the effectiveness of boundary regression target. by Fan Yang (1413)

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Segmentation results of DUKE dataset. by Fan Yang (1413)

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Evaluation of the effectiveness of the pruning ratio (r%). by Fan Yang (1413)

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