Traditional pattern recognition models work with hand crafted features and relatively simple trainable classifiers.
There are many limitations with these techniques:
- It is very tedious and costly to develop hand crafted features.
- The hand-crafted features are usually highly dependent on one application, and can not be easily applied to other applications/problems.
Deep learning has an inbuilt automatic multi stage feature learning process that learns rich features.