# CVB export each resolution filter images **URL:** \ **Category:** Programming Questions\ **Tags:** csharp\ **Created:** [February 7, 2020, 7:49am UTC](https://forum.commonvisionblox.com/t/cvb-export-each-resolution-filter-images/1048 "2020-02-07T07:49:37Z")\ **Posts on this page:** 1\ **Showing post:** 4
**Author:** ![illusive](https://yyz1.discourse-cdn.com/flex027/user_avatar/forum.commonvisionblox.com/illusive/32/61_2.png) [@illusive](https://forum.commonvisionblox.com/u/illusive)\ **Post date:** [February 9, 2020, 3:26pm UTC](https://forum.commonvisionblox.com/t/cvb-export-each-resolution-filter-images/1048/4 "2020-02-09T15:26:53Z")
> [@Jesse](#): > > 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](https://forum.commonvisionblox.com/t/polimago-creating-search-and-classification-training-sets-from-one-data-set/765) that produces a heat map which can give you a rough idea of what a Polimago classifier is sensitive to. In :cvb: 13.02.xxx and up the same functionality is also available inside the TeachBench application and as a tutorial for the [CVB.Net](http://CVB.Net) wrappers. --- _[View the full topic](https://forum.commonvisionblox.com/t/cvb-export-each-resolution-filter-images/1048)._