Tool Architectures

The different tool architectures correspond to different types of neural network models. If you want to get more accurate results at the expense of increased training and processing times, use the High Detail architectures. The High Detail and High Detail Quick architecture settings configure the tool to consider the entire image equally, while the Focused architecture setting is selective, focusing on the parts of the image with useful information. Due to this focus, the network can miss information, especially when the image has important details everywhere.

Focused

Focused tools use a feature sampler which samples important image pixel information by specific region, whose size and the density of sampling is user-defined. Then they use this information to learn about the labels you put on and the features critical to making correct decision in your vision problem. Generally, Focused tools are faster than High Detail tools but less accurate.

Focused architecture tools have the following features:

• The image data set includes a Training Set and a Test Set.

• The tool does not monitor validation loss. They do not use the Loss Inspector feature.

High Detail

High Detail tools sample image pixels from the entire view of an image, so it does not use a specific region-based sampler to acquire image pixel information. Like Focused tools, they use this information to learn about the labels you put on and the features critical to making correct decision in your vision problem. Generally, High Detail tools are slower than Focused tools but much more accurate.