From the course: Deep Learning: Image Recognition

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Designing a neural network architecture for image recognition

Designing a neural network architecture for image recognition - Python Tutorial

From the course: Deep Learning: Image Recognition

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Designing a neural network architecture for image recognition

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- [Instructor] Before we start coding our image recognition neural network, let's sketch out how it will work. This is the most basic neural network design. We feed it an image, it passes through one or more dense layers, and then it returns an output, but this kind of design doesn't work efficiently for images because objects can appear in lots of different places in an image. The solution is to add one or more convolutional layers to our neural network. These layers will help us detect patterns no matter where they appear in our image. It can be effective to put two or more convolutional layers in a row, so in our neural network, we'll add them in pairs. Our design so far, with two convolutional layers and the dense layer, would work for very simple images, but there are some tricks that we can add to our neural network to make it more efficient. The convolutional layers are looking for patterns in our image and recording whether or not they found those patterns in each part of our…

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