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- CADNet - GitHub
CADNet Code for Graph Representation of 3D CAD models for Machining Feature Recognition with Deep Learning paper This is an approach using graph neural networks to learning from planar B-Rep CAD models In the paper, focus was given towards the machining feature recognition task
- CADNET|3D模型识别数据集|深度学习数据集 - selectdataset. com
我们介绍了 CADNET 数据集,它是 43 个类别的 3,317 个 3D 工程模型的注释集合。 由于大型注释数据集的可用性以及 GPU 形式的足够计算能力,最近提出了许多基于深度学习的对象分类解决方案,特别是在图像和图形模型领域。
- News - CADNET Dataset
This is the repository for the ‘CADNET’ Dataset, associated with the paper “A Convolutional Neural Network Approach to the Classification of Engineering Models”
- 论文阅读 CAD-Net: A Context-Aware Detection Network . . . - CSDN博客
Extensive experiments over two public available datasets verify the uniqueness of object detection in remote sensing images, and also show that the proposed CADNet achieves superior object detection performance as compared with state-of-the-art techniques
- Hierarchical CADNet: Learning from B-Reps for Machining Feature . . .
Within each experiment, two versions of Hierarchical CADNet are tested One utilizes the edge convexity information denoted as Hierarchical CADNet (Edge) and the second uses only the B-Rep face adjacency matrix denoted Hierarchical CADNet (Adj)
- 数据集-OpenDataLab
我们介绍了 CADNET 数据集,它是 43 个类别的 3,317 个 3D 工程模型的注释集合。 由于大型注释数据集的可用性以及 GPU 形式的足够计算能力,最近提出了许多基于深度学习的对象分类解决方案,特别是在图像和图形模型领域。
- CAD-Net: A Context-Aware Detection Network for Objects in Remote . . .
The contributions of this work are fourfold First, it de-signs an innovative context-aware network to learn global and local contexts for optimal object detection in optical remote sensing images To the best of our knowledge, this is the first work to incorporate global and local contextual information for object detection in remote sensing images Second, it designs a spatial-and-scale
- GitHub - xupeiwust hierarchical-cadnet: Training Hierarchical GNN from . . .
This repo provides a code of the neural network described in the paper: Hierarchical CADNet: Learning from B-Reps for Machining Feature Recognition It is a deep learning approach to learn machining features from CAD models
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