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A team of mechanical engineers from Purdue University has undertaken the task of establishing a nearly 60,000-component, open-source, annotated database of 3D mechanical parts. The database aims to bring together applications in machine learning with the individual parts that enable those applications and more.
Though computer vision researchers often use machine learning principles to train computers to visually recognize distinct objects, few, Purdue reported in a press release, apply machine learning to mechanical parts — from gearboxes to clutches, and nuts to bolts.
After experimenting with the notion of visual searching for parts throughout the 2000s, teams led by Purdue’s Karthik Ramani determined that to…READ MORE