Deep Learning Skeletonization Model: Improve F-Score
2 weeks ago
Job summary
Skeletonisation of Natural images using Differentiable Rasterizer I have a skeletonization model trained with the DifferentiableSketching framework that extracts skeleton centerlines from images The model currently Trains on standard skeleton datasets Uses an encoder-decoder architecture with convolutional and RNN components Produces skeleton raster outputs but F-score metrics are well below published benchmarksGoal Improve the model's F score on all three datasets to be competitive with published benchmarks while eliminating overfitting such that Validation F score approaches or exceeds
Job description
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