Sparse Interactions, Receptive Field and Parameter Sharing是整个CNN深度网络的核心部分,我们用本文来具体分析其原理. 首先我们考虑Feedforward Neural Network,L层的输出矩阵,等于L层的输入矩阵与L层的权重矩阵做矩阵乘法,而后进行非线性变换.也就是说,L层的每一个输出数据,与L层的每一个输入数据都有关系.若输入数据是m维,输出数据是n维,则存在m*n个权重项来表征输入与输出间的关系.所以,Forward-prop…
An Intuitive Explanation of Convolutional Neural Networks https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/ Posted on August 11, 2016 by ujjwalkarn What are Convolutional Neural Networks and why are they important? Convolutional Neural…
https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/ An Intuitive Explanation of Convolutional Neural Networks Posted on August 11, 2016 by ujjwalkarn What are Convolutional Neural Networks and why are they important? Convolutional Neural…
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks 理解深度卷积神经网络中的有效感受野 Abstract摘要 We study characteristics of receptive fields of units in deep convolutional networks. The receptive field size is a crucial issue in many vis…
CNN 大概是目前 CV 界最火爆的一款模型了,堪比当年的 SVM.从 2012 年到现在,CNN 已经广泛应用于CV的各个领域,从最初的 classification,到现在的semantic segmentation, object detection,instance segmentation,super resolution 甚至 optical flow 都能看的其身影.还真是,无所不能. 虽然 CNN 的应用可以说是遍地开花,但是细究起来,可以看到 CNN 的基本模型还是万变不离其宗…
Table of Contents: Architecture Overview ConvNet Layers Convolutional Layer Pooling Layer Normalization Layer Fully-Connected Layer Converting Fully-Connected Layers to Convolutional Layers ConvNet Architectures Layer Patterns Layer Sizing Patterns C…
Note This section assumes the reader has already read through Classifying MNIST digits using Logistic Regression and Multilayer Perceptron. Additionally, it uses the following new Theano functions and concepts: T.tanh, shared variables, basic arithme…
About this Course This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applica…
A Beginner's Guide To Understanding Convolutional Neural Networks Introduction Convolutional neural networks. Sounds like a weird combination of biology and math with a little CS sprinkled in, but these networks have been some of the most influential…
Adit Deshpande CS Undergrad at UCLA ('19) Blog About A Beginner's Guide To Understanding Convolutional Neural Networks Part 2 Introduction Link to Part 1 In this post, we’ll go into a lot more of the specifics of ConvNets. Disclaimer: Now, I do reali…