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在深度学习中对单元进行分类以进行图像分类

[英]classify the units in Deep learning for image classification

原文 2015-04-29 03:32:12 0 2 classification/ deep-learning/ dbn

Suppose we have a database with 10 classes, and we do classification test on it by Deep Belief Network or Convolutional Neural Network. 假设我们有一个包含10个类的数据库，并通过Deep Belief网络或卷积神经网络对其进行分类测试。 The question is that how we can understand which neurons in the last layer are related to which object? 问题是我们如何才能理解最后一层中的哪些神经元与哪个对象有关？ In one of the post, a person wrote " to understand which neurons are for an object like shoes and which ones are not you will put that all units in the last layer to another supervised classifier(this can be anything like multi-class-SVM or a soft-max-layer). I do not know how it should be done? I do need more expansion. 在其中一篇文章中，一个人写了“以了解哪些神经元是用于鞋子等对象的，哪些不是，您将把最后一层中的所有单元放到另一个监督的分类器中（这可以是多类SVM之类的东西或soft-max-layer），我不知道应该怎么做？我确实需要更多扩展。

2 个解决方案

If you have 10 classes, make your last layer have 10 neurons and use the softmax activation function. 如果您有10个类别，请使您的最后一层具有10个神经元，并使用softmax激活功能。 This will make sure that they all lie between 0 and 1 and add up to 1. Then, simply use the index of the neuron with the largest value as your output class. 这样可以确保它们都在0到1之间并且加起来等于1。然后，只需使用具有最大值的神经元的索引作为输出类即可。

You can look into class activation maps which does something similar to what you are asking for. 您可以查看类激活映射 ，该映射的功能类似于您所要求的。 Here is an insightful blog post explaining CAM s 这是解释CAM的有见地的博客文章。

没有标签的深度学习分类 - Deep learning classification with no labels

深度学习网络分类 - Deep learning network for classification

如何使用keras深度学习对图像序列进行分类 - How to classify sequence of images with keras deep learning

使用深度学习进行性别检测和年龄分类 - Gender detection and age classification using deep learning

是否有用于实例分类的深度学习模型，而不是边界框？ - Any deep learning models for instance classification in an image, rather than bounding box?

深度学习分类中如何处理类之间的相关性？ - How to deal with correlation between classes in deep learning classification?

关于分类而不是使用深度学习进行回归的问题 - Issues regarding classification instead of regression using deep learning

python中如何结合深度学习模型和传统机器学习模型的分类结果 - How to combine the classification results of deep learning models and traditional machine learning models in python

使用深度学习防止在多类分类中过度拟合特定类 - Prevent overfitting to specific class in multi-class classification using deep learning

机器学习：图像分类：CNN：如何识别“红色汽车”？ - Machine Learning: Image Classification: CNN: How to identify Just Red Cars?

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相关问题 没有标签的深度学习分类 - Deep learning classification with no labels 深度学习网络分类 - Deep learning network for classification 如何使用keras深度学习对图像序列进行分类 - How to classify sequence of images with keras deep learning 使用深度学习进行性别检测和年龄分类 - Gender detection and age classification using deep learning 是否有用于实例分类的深度学习模型，而不是边界框？ - Any deep learning models for instance classification in an image, rather than bounding box? 深度学习分类中如何处理类之间的相关性？ - How to deal with correlation between classes in deep learning classification? 关于分类而不是使用深度学习进行回归的问题 - Issues regarding classification instead of regression using deep learning python中如何结合深度学习模型和传统机器学习模型的分类结果 - How to combine the classification results of deep learning models and traditional machine learning models in python 使用深度学习防止在多类分类中过度拟合特定类 - Prevent overfitting to specific class in multi-class classification using deep learning 机器学习：图像分类：CNN：如何识别“红色汽车”？ - Machine Learning: Image Classification: CNN: How to identify Just Red Cars?

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