Why are CNNs so powerful?

CNNs are among the most powerful machine learning models at solving challenging problems such as image classification, object detection, object segmentation, video processing, natural language processing, and speech recognition. Their success is attributed to various factors, such as the following:

• Weight sharing: This makes CNNs parameter-efficient, that is, different features are extracted using the same set of weights or parameters. Features are the high-level representations of input data that the model generates with its parameters.
• Automatic feature extraction: Multiple feature extraction stages help a CNN to automatically learn feature representations in a dataset.
• Hierarchical learning: The multi-layered CNN structure helps CNNs to learn low-, mid-, and high-level features.
• The ability to explore both spatial and temporal correlations in the data, such as in video processing tasks.

Besides these pre-existing fundamental characteristics...