Cross-dataset evaluation: Performance of WA-YOLO and YOLOv8 on the COCO128 dataset. by LinNa Li (5665885)

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Ablation experiments on custom dataset. by LinNa Li (5665885)

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Comparison of detection results of mainstream models on the custom dataset. by LinNa Li (5665885)

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Shows the detonator detection results of the improved model in different scenarios at the blasting site. by LinNa Li (5665885)

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Module ablation study. by LinNa Li (5665885)

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The training results of WA-YOLO and YOLOv8 on the custom blasting site dataset are presented, where (a) shows the mAP_0.5 comparison, and (b) illustrates the box loss tra... by LinNa Li (5665885)

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Comparison of detection results of mainstream models on the VOC2012 dataset. by LinNa Li (5665885)

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Overlap between predicted box and ground truth box. by LinNa Li (5665885)

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The structure of the spatial attention module. by LinNa Li (5665885)

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Statistical analysis of different datasets. by LinNa Li (5665885)

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Active Multi-Resolution Learning of Neural Operators by Shandian Zhe (19346278)

“…Specifically, we propose a probabilistic multi-resolution FNO and use <i><u>ensemble Monte-Carlo </u></i>to develop an effective posterior inference algorithm. …”

DataSheet1_Multi-Objective Optimization Design of Ladle Refractory Lining Based on Genetic Algorithm.docx by Ying Sun (23237)

“…<p>Genetic algorithm is widely used in multi-objective mechanical structure optimization. …”

Table_5_Machine learning algorithms assisted identification of post-stroke depression associated biological features.XLSX by Xintong Zhang (1536829)

“…Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and random forest, were used to identify signature genes. …”

Table_3_Machine learning algorithms assisted identification of post-stroke depression associated biological features.XLSX by Xintong Zhang (1536829)

“…Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and random forest, were used to identify signature genes. …”

Table_2_Machine learning algorithms assisted identification of post-stroke depression associated biological features.XLSX by Xintong Zhang (1536829)

“…Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and random forest, were used to identify signature genes. …”

Table_1_Machine learning algorithms assisted identification of post-stroke depression associated biological features.XLSX by Xintong Zhang (1536829)

“…Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and random forest, were used to identify signature genes. …”

Table_6_Machine learning algorithms assisted identification of post-stroke depression associated biological features.docx by Xintong Zhang (1536829)

“…Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and random forest, were used to identify signature genes. …”

Table_4_Machine learning algorithms assisted identification of post-stroke depression associated biological features.XLSX by Xintong Zhang (1536829)

“…Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and random forest, were used to identify signature genes. …”

Variation in GMs prediction values from 25-fold cross validation. by E. Passmore (18010656)

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GMs prediction and motor development at 2 years. by E. Passmore (18010656)

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