Unsupervised methods, on the other hand do not require you to mark the area or choose regions manually. The process of identifying segments is fully automatic, with some hyper-parameters available to set the minimum segment size and detail level.
Unsupervised methods
The graph-based approach
This time, will be using the Felzenszwalb algorithm, which is an unsupervised and efficient graph-based approach. It was proposed by P.F Felzenszwalb and Huttenlocher in 2004 and has been actively used in computer vision since. The benefits of using the Felzenszwalb algorithm are as follows:
- A small number of hyperparameters
- Fast and linear execution time
- Preserves details in low variability areas
Julia implements Felzenszwalb algorithms...
