In simple words: Inception combines visual information from different scales.
The main idea
Inception is a family of CNN architectures that combines operations with different receptive fields within a module. This lets a model consider smaller and larger visual patterns together.
Where it fits
The supplied notes name Inception among important CNN architectures but do not explain it in detail. At this basic level, remember that VGG repeats small filters, Inception mixes scales, ResNet adds shortcuts, and EfficientNet balances model size and image resolution.
See the flow
image→parallel feature scales→combined features
Simple example
A photo may contain tiny text on a box and a large vehicle. Different scale features help describe both.
Remember: Inception combines visual information from different scales.