We are a Norwegian Center for Research-based Innovation that aims at unlocking the potential of visual intelligence across our main innovation areas medicine and health, marine science, energy sector, and earth observation by enabling the next generation deep learning methodology for extracting knowledge from complex image data.
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Hi Jon, your talk about deep learning algorithms was interesting this is something I would like to learn more about. Did you apply your experimental models to the k space domain by regressing the images back into the data domain or were you able to use the raw data. I am concern with the pixelated under sampling (discussed at time point~5 min and 40s) is this is not something we could reproduce clinically. We can only fill k space linearly, concentrically or radially. The parallel undersampling is something we could mimic as we can opt to reduce k space filling in the phase encoding direction. I look forward to your response Kind regards Darren
Can you make a video about probabilistic functions and artificial neural networks? why to specifically take insipiration from neural network to solve probabilisting problrms ?
Thanks for the comment. I did not realize this while speaking, but I agree with your comment. The location of the mic should be readjusted for the next presentation. Hope the generated subtitle helps.
I love this professor's presentation but it can sometimes be difficult to understand what he is saying. It would really help if there was a written transcript of the presentation.
Very interesting talk. Are there any easy to understand sources so I can learn more about the approaches Raul mentioned or about the field in general? So far I have always ignored noisiness of my data when training models.
What sense does image segmentation make as a generative model problem? I imagine you could translate any problem into a generative model problem. E.g. instead of classification we can do generation of class conditioned on input image. Does formulating it in such a way makes more sense for image segmentation than for image classification or was that the point that any problem can be formulated this way?
Thanks for the upload, keep up the good work!! You need more views. Did you ever look into using PromoSM!?? It will help you get your videos higher in the RU-vid search results!
