my version
This report contains the results of trained of a hyperparameter sweep for exploring a model designed for segmentation of 3D point cloud data. The runs are grouped by category to get an initial understanding of the dataset.
Created on December 7|Last edited on December 7
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Section 1
Showing first 10 runs
Featured Report
This report is a saved snapshot of Nick's research. He's published this example so you can see how to use W&B to visualize training and keep track of your work. Feel free to add a visualization, click on graphs and data, and play with features. Your edits won't overwrite his work.
Project Description
The goal of this model is to take input of a point cloud representing a real world object and provide segmentation of the object into different parts. 3D Semantic segmentation is a foundational problem of computer vision and has applications from self driving cars to medical diagnoses
Sweep: 2jt716r2
89
Section 2
Run set 1
55
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