Part machining feature recognition based on a deep learning method
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Industrial and Manufacturing Engineering,Software
Link
https://link.springer.com/content/pdf/10.1007/s10845-021-01827-7.pdf
Reference25 articles.
1. Cao, W., Robinson, T., Hua, Y., Boussuge, F., Colligan, A. R., & Pan, W. (2020). Graph representation of 3D CAD models for machining feature recognition with deep learning. In Proceedings of the ASME 2020 international design engineering technical conferences and computers and information in engineering conference, 46th design automation conference (DAC) (Vol. 11A). https://doi.org/10.1115/DETC2020-22355.
2. Ghadai, S., Balu, A., Sarkar, S., & Krishnamurthy, A. (2018). Learning localized features in 3D cad models for manufacturability analysis of drilled holes. Computer Aided Geometric Design, 62(MAY), 263–275.
3. Gong, Z., Zhong, P., Yu, Y., Hu, W., & Li, S. (2019). A CNN with multiscale convolution and diversified metric for hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing, 57(6), 3599–3618.
4. Hashemi, A., Dowlatshahi, M. B., & Nezamabadi-pour, H. (2020). Mgfs: A multi-label graph-based feature selection algorithm via pagerank centrality. Expert Systems with Applications, 142, 46–53.
5. Joshi, S., & Chang, T. C. (1988). Graph-based heuristics for recognition of machined features from a 3D solid model. Computer-Aided Design, 20(2), 58–66.
Cited by 23 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. An Edge-Based Neural Network Architecture for Instance Segmentation in Machining Feature Recognition;2024-09-13
2. An Agent-Based Method for Feature Recognition and Path Optimization of Computer Numerical Control Machining Trajectories;Sensors;2024-09-03
3. A review and assessment of 3D CAD model retrieval in machine-part design;International Journal of Computer Integrated Manufacturing;2024-07-23
4. BrepMFR: Enhancing machining feature recognition in B-rep models through deep learning and domain adaptation;Computer Aided Geometric Design;2024-06
5. Adaptive recognition of machining features in sheet metal parts based on a graph class-incremental learning strategy;Scientific Reports;2024-05-09
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3