Deep Learning for Computer Vision

Choosing the right model

There are a lot of options for architectures. Based on the flexibility of deployment, you can choose the model. Remember that convolution is smaller and slower, but dense layers are bigger and faster. There is a trade-off between size, runtime, and accuracy. It is advisable to test out all the architectures before the final decision. Some models may work better than others, based on the application. You can reduce the input size to make the inference faster. Architectures can be selected based on the metrics as described in the following section.