相关实验视频

Updated: May 3, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

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用卷积和混合模型对可解释的组织学分类进行透规范化的注意

Pedro L Miguel1, Leandro A Neves1, Alessandra Lumini2

  • 1Department of Computer Science and Statistics (DCCE), São Paulo State University (UNESP), Rua Cristóvão Colombo, 2265, São José do Rio Preto 15054-000, São Paulo, Brazil.

Entropy (Basel, Switzerland)
|July 29, 2025
PubMed
概括

这项研究引入了一个新的框架,以提高深度学习模型在组织学图像分类中的可解释性. 该方法增强可视化热图,提供更清晰的见解,而不牺牲准确性.

关键词:
促进CAM 促进CAM这是Grad-CAM.注意力分支注意力分支卷积神经网络是一种卷积神经网络.组织学图像 组织学图像视觉变压器 视觉变压器

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