<p>You can try using Mask R-CNN. Refer to these links for your understanding:</p>
<ul>
<li><a href="https://github.com/matterport/Mask_RCNN" rel="nofollow noreferrer">https://github.com/matterport/Mask_RCNN</a></li>
<li><a href="https://arxiv.org/abs/1703.06870" rel="nofollow noreferrer">https://arxiv.org/abs/1703.06870</a></li>
</ul>
<p>Basically, you need to make an annotation (polygonal) for your dataset with tools like VIA image annotation tool (<a href="https://www.robots.ox.ac.uk/%7Evgg/software/via/" rel="nofollow noreferrer">https://www.robots.ox.ac.uk/~vgg/software/via/</a>) or MakeSense (<a href="https://www.makesense.ai/" rel="nofollow noreferrer">https://www.makesense.ai/</a>). 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.</p>
ROI detection - Deep learning -References
<p>I know nothing on the subject of deep learning.</p>
<p>I am looking for references to <strong>build a deep learning algorithm</strong> to detect ROI in given images. My goal is to <strong>compare deep learning algorithms with usual image processing algorithms I have already made</strong>.
The input images look like this :</p>
<p><a href="https://i.stack.imgur.com/YYDHY.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/YYDHY.jpg" alt="enter image description here" /></a></p>
<p>The output of the algorithm should look like this :</p>
<p><a href="https://i.stack.imgur.com/krdit.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/krdit.jpg" alt="enter image description here" /></a></p>
<p>Q1: Do you have any <strong>references</strong> that if I read them would let me build such a <strong>deep learning algorithm</strong> from start to finish ?</p>
<p>Q2: Otherwise, do such algorithms already exist and are freely available ? (<strong>Note:</strong> Such algorithms should produce precise ROI detection not broad rectangles encircling the bright regions).</p>