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Entropy-Based Convolutional Layer Selection for Transfer Learning in Brain Tumor Detection
DOI:10.1007/s13369-026-11263-5.png)
摘要
En 中文
基于熵的微调方法在脑肿瘤分类中的应用:使用ResNet18和ResNet34的迁移学习研究
Keyword:
Brain tumor
Transfer learning
Entropy
Deep learning
Artificial intelligence
AI总结
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期刊
A
IF:
2.9
论文数:
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被引数:
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引用论文
Wider or Deeper: Revisiting the ResNet Model for Visual Recognition更广泛或更深入: 重新审视视觉识别的ResNet模型
PATTERN RECOGNITION
IF7.6
ResNet and its application to medical image processing: Research progress and challengesResNet及其在医学图像处理中的应用: 研究进展与挑战
Jointly Constrained Group Sparse Connectivity Representation Improves Early Diagnosis of Alzheimer's Disease on Routinely Acquired T1-Weighted Imaging-Based Brain Network联合约束的组稀疏连接性表示在常规获取的T1加权成像基础脑网络中改善了阿尔茨海默病的早期诊断
BrainCDNet: a concatenated deep neural network for the detection of brain tumors from MRI imagesBrainCDNet:一种用于检测MRI图像中脑肿瘤的级联深度神经网络

