ROI detection - Deep learning -References

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I know nothing on the subject of deep learning.

I am looking for references to build a deep learning algorithm to detect ROI in given images. My goal is to compare deep learning algorithms with usual image processing algorithms I have already made. The input images look like this :

enter image description here

The output of the algorithm should look like this :

enter image description here

Q1: Do you have any references that if I read them would let me build such a deep learning algorithm from start to finish ?

Q2: Otherwise, do such algorithms already exist and are freely available ? (Note: Such algorithms should produce precise ROI detection not broad rectangles encircling the bright regions).

2 Answers

You can try using Mask R-CNN. Refer to these links for your understanding:

Basically, you need to make an annotation (polygonal) for your dataset with tools like VIA image annotation tool (https://www.robots.ox.ac.uk/~vgg/software/via/) or MakeSense (https://www.makesense.ai/). These are the open source tools that I can recommend. After training, the network can predict the bounding box as well as the boundary of the detected objects.

Your task is easy, don't worry about knowing anything about the topic, as your image shows what you are trying to achieve, I would suggest you try using semantic segmentation, you can search on youtube or read about Faster R-CNNthey are kinda related to what you want to do. Then you can compare the output results with the regular image processing.

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