CNN model configuration: advice

Hi,
Assume that a CNN model is to be developed to recognize commercial domestic planes flying in the sky. The training data should include images of flying domestic planes for true positives. Additionally, it should encompass other types of aircrafts, such as private jets and helicopters. Should the training data also include instances with no flying aircraft so that the output layer has two outputs: Domestic plane and Non-domestic plane? Or would it be better to have three outputs in the output layer: Commercial domestic plane, Non-commercial domestic, Non flying aircraft?

Cheers

Hi @K_M23 Welcome to the Tensorflow Forum ,

In this case, it would be better to have three outputs in the output layer: Commercial domestic plane, Non-commercial domestic plane, and Non-flying aircraft. This approach allows for better granularity in classification and ensures that the model can distinguish between different types of aircraft and their flying status effectively.

Thank You !