بدائل البحث:
significant progressive » significant progress (توسيع البحث), significant protective (توسيع البحث), significant processes (توسيع البحث)
progressive decrease » progressive decline (توسيع البحث)
shape decrease » shape increases (توسيع البحث), step decrease (توسيع البحث), showed decreased (توسيع البحث)
small decrease » small increased (توسيع البحث)
significant progressive » significant progress (توسيع البحث), significant protective (توسيع البحث), significant processes (توسيع البحث)
progressive decrease » progressive decline (توسيع البحث)
shape decrease » shape increases (توسيع البحث), step decrease (توسيع البحث), showed decreased (توسيع البحث)
small decrease » small increased (توسيع البحث)
-
101
-
102
-
103
-
104
-
105
-
106
-
107
-
108
-
109
-
110
-
111
-
112
Architecture of Swin-T model.
منشور في 2024"…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. …"
-
113
Model the experimental results curve.
منشور في 2024"…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. …"
-
114
Results of comparison experiments.
منشور في 2024"…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. …"
-
115
Architecture of Swin Transformer Block.
منشور في 2024"…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. …"
-
116
Disease distribution map of the GZDL-BD.
منشور في 2024"…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. …"
-
117
Token merging module.
منشور في 2024"…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. …"
-
118
Comparative results of the ablation experiments.
منشور في 2024"…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. …"
-
119
-
120