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| I'm training UNET neural networks for muscle segmentation ([link][1]) and implementing LearningRateSchedules that hopefully help with the last extra bit of performance I need. However when implementing it i observed some weird behaviour. For... |
| Awesome!! I'm well aware I'm pushing the limits by finding the most expensive renders each time ;) and are very happy that each time you are providing me with solutions. Exactly what i needed, this trick is speeding up my other renders as well. ... |
| Assuming you only have discrete data and no access tot the function that generates the data, ``` colF = Interpolation[data[[All, {1, 3}]]]; ListLinePlot[data[[All, {1, 2}]], ColorFunction -> Function[{x}, If[colF[x] False] ``` with the... |
| ![enter image description here][1] &[Wolfram Notebook][2] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=flowchart_seg.gif&userId=1332602 [2]:... |
| Think it is `ListCorrelate `. |
| Does anyone have a better solution for reading and writing half-precision float16? As far as I can find Mathematica does not support this at the moment or am I missing something? Currently, I'm reading the data as "UnsignedInteger16" and then... |
| Hi Yuzhu, Finally, I came around to testing the performance of my tube renders in v 14.0. As you promised the memory use has decreased substantially. Before I had crashes rendering scenes of 16MB with around 7.5K tubes I can now render way... |
| yes 13.3 on windows 10 |
| *MODERATOR NOTE: This is the notebook used in the livestream "QMRITools: Processing Quantitative MRI Data" on Wednesday, September 27 -- a part of Wolfram R&D livestream series announced and scheduled here: https://wolfr.am/RDlive. Subscribe to... |
| Hi all, tomorrow I’ll be presenting on QMRITools: Processing Quantitative MRI Data at 11 AM CST. I will be discussing how i develop and maintain [my paclet][1] and showcasing some functions I use in my [research][2], such as [muscle fibre... |