Presentation
DeepMill++: Neural Guidance Meets Rasterization for Efficient Accessibility Analysis
SessionFabrication
DescriptionWe introduce DeepMill++, a conservative and highly efficient framework for cutter accessibility analysis on arbitrary triangular meshes. DeepMill++ reformulates accessibility and occlusion detection as a rasterization-based visibility and depth pooling problem. DeepMill++ achieves up to 9.5× speedup over state-of-the-art geometric methods, while maintaining 97.5% conservative accessibility accuracy.
Event Type
Technical Paper
TimeMonday, 20 July 20264:25pm - 4:35pm PDT
LocationRoom 403 B
Digital Library
PDF
Session Time & Location
Sunday, 19 July 20266:00pm - 8:45pm PDTHall K
Monday, 20 July 20263:45pm - 5:35pm PDTRoom 403 B
Artificial Intelligence/Machine Learning
Fabrication
Geometry
Modeling
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