Recommendations on how to go from basics (being able to fine-tune pretrained ImageNet/Inceptionv3 with new data etc) to a real project? I'd like to play with semantic segmentation of satellite images (hyperspectral). Any pointers?
That's really what this course tries to do. Lesson 7 shows how to do localization in a couple of different ways. And in every lesson I try to show how to get a state of the art result on a real dataset, showing the process from end to end. Jupyter notebooks are available for all of these projects.
(We'll be looking at more segmentation techniques in the next part of the course next year.)
Recommendations on how to go from basics (being able to fine-tune pretrained ImageNet/Inceptionv3 with new data etc) to a real project? I'd like to play with semantic segmentation of satellite images (hyperspectral). Any pointers?