Training and optimizing a machine learning model to generate 3D voxels from 2D images using auto-encoder architecture for custom-made hearing aids manufacturing
End-to-end solution for 3D prints custom-made hearing aids. The goal was to develop a machine learning model capable of generating 3D voxel representations from 2D images, enabling automated 3D reconstruction for hearing aid manufacturing.
Successfully upgraded voxel resolution from 32³ to 128³, significantly improving 3D reconstruction detail
Implemented comprehensive data augmentation from STL files with multi-angle image generation
Optimized training process across multiple epochs for maximum performance
Achieved ~60% accuracy in testing phase - identified areas for future improvement
Learned to modify and optimize auto-encoder architectures for specific 3D reconstruction tasks, including resolution enhancement techniques.
Developed expertise in creating effective training datasets from 3D models, including multi-angle image generation and STL file processing.
Gained valuable experience in model evaluation and identifying areas for improvement when results don't meet production requirements.