Author: datahacker.rs

#013 B CNN AlexNet

\(AlexNet \) In the previous posts we talked about LeNet−5. Let’s now see one more example of a convolutional neural network. The second convolutional neural network that we are going to present is \(AlexNet \) neural network. An input to this neural network is \(227\times227\times3\). We have a color image as an input and that is why we have \(3 \) channels. \(AlexNet \) architecture Let’s explore the architecture of this convolutional neural network. \(Conv\enspace1\) First,…
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#013 A CNN LeNet-5

\(LeNet-5 \) The goal of \(LeNet-5 \) was to recognize handwritten digits. So, it takes as an input \(32\times32\times1 \) image. It is a grayscale image, thus the number of channels is \(1 \). Here is a picture of it’s arhitecture.  \(LeNet-5 \) architecture In the first step we use \(6\enspace5 \times 5\) filters with a stride \(s=1 \) and \(no\enspace padding\). Therefore we end up with a \(28 \times 28 \times 6 \) volume.…
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#012 CNN Convolutional Neural Networks – An Overview

Last time we saw we are Convolutions very useful when we include them in our neural networks. In this post we will give just an overview of the 11 Convolutional Neural Network architectures.   Convolutional Neural Netwok Academic Paper Authors Python experiments    LeNet-5  ” Gradient-based Learning Applied to Document Recognition “ Yann LeChun, Leon Bottou, Youshua Bengaio, Patric Haffner    AlexNet  “ImageNet Classification with Deep Convolutional Neural Networks” Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton  …
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#011 CNN Why convolutions ?

Why convolutions ?  In this post we will talk about why  convolutions or convolutional neural networks work so well in a computer vision. Convolutions are very useful when we include them in our neural networks. There are two main advantages of \(Convolutional \) layers over \(Fully\enspace connected\) layers: parameter sharing and sparsity of connections. We can illustrate an example. Let’s say that we have a \(32\times32\times3\) dimensional image. This actually comes from the example from the previous…
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#010 CNN An Example of a Neural Network

Convolutional Neural Network – An Example In previous posts (CNN 004, CNN 005 and CNN 009) we have defined all building blocks for building a full convolutional neural network. Let’s now look at an example of a convolutional neural network (CNN). Let’s say that we have a \(32 \times 32 \times 3 \) dimensional image as an input to the CNN. So it’s an RGB image and supoose we want to try to do a handwritten…
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