Mouldboard plough body working resistance response surface. by Xueting Ma (390540)

Subjects:

The composition of the body of a mouldboard plough. by Xueting Ma (390540)

Subjects:

Mouldboard plough body resistance diagram with different mouldboard plough surface convex structure radii. by Xueting Ma (390540)

Subjects:

Soil disturbance response surface curved surface. by Xueting Ma (390540)

Subjects:

ANOVA for the quadratic polynomial regression model of mouldboard plough body working resistance. by Xueting Ma (390540)

Subjects:

Selection of soil particle sampling points. by Xueting Ma (390540)

Subjects:

The overall structure of the device. by Xueting Ma (390540)

Subjects:

Static analysis results. by Xueting Ma (390540)

Subjects:

Changes in mouldboard plough body resistance at different lugs angles. by Xueting Ma (390540)

Subjects:

Correlation and principal component analysis. by Jie Wei (264772)

Mediation effect of muscle strength on the associations of obesity with incidence of knee OA. by Laijun Yan (19797455)

Frontier analysis of injuries’ burden caused by fire, heat, and hot substances from 1990 to 2021. by Shi Huang (125861)

Development and Use of a Galectin-1-Specific Nanobody for Tumor Imaging and Elucidating the Role of Galectin‑1 in Cancer by Philippine Granger Joly de Boissel (21688159)

Subjects:

Architecture of Swin-T model. by Wen-Qing Huang (5258126)

“…However, traditional methods heavily rely on low-level image analysis, handcrafted features, and classical classifiers, leading to limited effectiveness and poor generalization in complex scenarios. Although significant progress has been made with deep learning methods, challenges persist in handling high-resolution images and diverse disease types. …”

Model the experimental results curve. by Wen-Qing Huang (5258126)

“…However, traditional methods heavily rely on low-level image analysis, handcrafted features, and classical classifiers, leading to limited effectiveness and poor generalization in complex scenarios. Although significant progress has been made with deep learning methods, challenges persist in handling high-resolution images and diverse disease types. …”

Results of comparison experiments. by Wen-Qing Huang (5258126)

“…However, traditional methods heavily rely on low-level image analysis, handcrafted features, and classical classifiers, leading to limited effectiveness and poor generalization in complex scenarios. Although significant progress has been made with deep learning methods, challenges persist in handling high-resolution images and diverse disease types. …”

Architecture of Swin Transformer Block. by Wen-Qing Huang (5258126)

“…However, traditional methods heavily rely on low-level image analysis, handcrafted features, and classical classifiers, leading to limited effectiveness and poor generalization in complex scenarios. Although significant progress has been made with deep learning methods, challenges persist in handling high-resolution images and diverse disease types. …”

Disease distribution map of the GZDL-BD. by Wen-Qing Huang (5258126)

“…However, traditional methods heavily rely on low-level image analysis, handcrafted features, and classical classifiers, leading to limited effectiveness and poor generalization in complex scenarios. Although significant progress has been made with deep learning methods, challenges persist in handling high-resolution images and diverse disease types. …”

Token merging module. by Wen-Qing Huang (5258126)

“…However, traditional methods heavily rely on low-level image analysis, handcrafted features, and classical classifiers, leading to limited effectiveness and poor generalization in complex scenarios. Although significant progress has been made with deep learning methods, challenges persist in handling high-resolution images and diverse disease types. …”

Comparative results of the ablation experiments. by Wen-Qing Huang (5258126)

“…However, traditional methods heavily rely on low-level image analysis, handcrafted features, and classical classifiers, leading to limited effectiveness and poor generalization in complex scenarios. Although significant progress has been made with deep learning methods, challenges persist in handling high-resolution images and diverse disease types. …”