Hi Sir:
CVB detects relevant features by non-linear Multi-Resolution Filter (MRF). I want to know what features learned by CVB, so could CVB C# Dll export each resolution filter images?
thanks.
Hi Sir:
CVB detects relevant features by non-linear Multi-Resolution Filter (MRF). I want to know what features learned by CVB, so could CVB C# Dll export each resolution filter images?
thanks.
Hi @Jesse,
I am sorry but the precise nature of the MRF filters is not disclosed by STEMMER IMAGING and to prevent reverse engineering no function that exports the MRF results exists in the API.
Hi illusive:
Thank you for your reply. Because I want to check CVB Polimago Classification and Regression really learn the features from I fed images, Can you give me some ways or suggestion to check the features is already be learned.
The notion of a learned feature is not entirely straightforward with a tool like Polimago. Polimago at least in in terms of how it works - is more similar to a neural network than it is to a tool like e.g. Minos and ShapeFinder. Minos and ShapeFinder are using feature lists that are verified versus image content, so you can - in principle - tell which features have been found and which features haven’t (both tools in fact don’t collect that information but that is for performance reasons) and your classifier operates with a definitive list of features it is looking for.
This is not the case for Polimago: Polimago uses the result of the MRF sequence as the input vector to a classification learning engine based on Tikhonov’s regulratization, and the classification engine then tries to approximate a function mapping an input vector to a result scalar (the output of which is your classification result) using the training data. This function effectively becomes your classifier (in the case of Polimago this would be a high dimension linear function; in deep learning you’d have a trained neural network here). At no point Polimago is using a list of features, and there is no definitive way to tell what precisely it is looking for - the classifier has to a fair extent to be treated as a black box.
There are ways, however, to get a rough idea of what is going on: @MartinK has posted a C# program here that produces a heat map which can give you a rough idea of what a Polimago classifier is sensitive to. In 13.02.xxx and up the same functionality is also available inside the TeachBench application and as a tutorial for the CVB.Net wrappers.