B.5: PointNet++: Difference between revisions
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• '''Short Description''': | • '''Short Description''': | ||
Deep Hierarchical Feature Learning on Point Sets in a Metric Space. An example of 3D segmentation Deep Learning architecture | |||
• '''Reference, URL''': https://arxiv.org/abs/1706.02413 | • '''Reference, URL''': https://arxiv.org/abs/1706.02413 | ||
• ''' | • '''Applicable Business Category''': Manufacturing (WEEE & Battery) | ||
• '''Application in relevant Projects/Initiatives''': | • '''Application in relevant Projects/Initiatives''': No | ||
• '''Type''': ML Model | • '''Asset Type''': ML Model | ||
• '''AI Breadth''': Deep Learning, Neural networks | • '''AI Breadth''': Deep Learning, Neural networks | ||
| Line 15: | Line 15: | ||
• '''Learning Ability''': Supervised learning | • '''Learning Ability''': Supervised learning | ||
• '''Related technologies''': | • '''Related technologies''': Deep Hierarchical Feature Learning | ||
• '''Applicable Research Area''': | • '''Applicable Research Area''': Physical AI | ||
• '''Applicable Technical Category''': | • '''Applicable Technical Category''': Computer Vision | ||
• '''License Information''': MIT license (MIT) | • '''License Information''': MIT license (MIT) | ||
| Line 29: | Line 25: | ||
• '''Related to circularity and sustainability''': No | • '''Related to circularity and sustainability''': No | ||
• '''Audience''': | • '''Audience''': Manufacturers | ||
Latest revision as of 10:03, 27 December 2024
• Short Description: Deep Hierarchical Feature Learning on Point Sets in a Metric Space. An example of 3D segmentation Deep Learning architecture
• Reference, URL: https://arxiv.org/abs/1706.02413
• Applicable Business Category: Manufacturing (WEEE & Battery)
• Application in relevant Projects/Initiatives: No
• Asset Type: ML Model
• AI Breadth: Deep Learning, Neural networks
• Learning Ability: Supervised learning
• Related technologies: Deep Hierarchical Feature Learning
• Applicable Research Area: Physical AI
• Applicable Technical Category: Computer Vision
• License Information: MIT license (MIT)
• Related to circularity and sustainability: No
• Audience: Manufacturers
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