ROI detection - Deep learning -References

Question

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 :

The output of the algorithm should look like this :

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).

Answer 1

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

• https://github.com/matterport/Mask_RCNN
• https://arxiv.org/abs/1703.06870

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.

Answer 2

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.