Dl
vs. stable diffusion. EXPERIMENTS
We attempted this challenge as part of our Deep Learning and Neural Networks Major Project.
The notebook can be found at /code/10khrs-ai-ml-dl/projects/kits19/report.html, which contains implementation details of U-Net, SamNet, VGG-Net and nnU-Net.
The corresponding report, containing a literature review along with other scientific details is embedded below:
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Non-descriptive frisbee stats
A computer vision model that takes in streamed games and outputs a player statistic that factors in non-descriptive events — i.e. giving the correct call at the correct time, or poaching in the lane to force a bad throw.
I expect this to be trained using a transformer and written in Python. It is inspired by Andrew Wood's analytical Ultimate dream.
OCR
This was one of the first times I fell in love with Machine Learning, without knowing that the magic came from Machine Learning methods.
I simply had a `pdf` file with handwritten or scanned text, and desperately wanted to find something within the document without having to do it manually.
I google online for an OCR; upload my file; download it back again, and hey presto — such magical, accurate results!