Hierarchical CADNet: Learning from B-Reps for Machining Feature Recognition

Autor: Andrew R. Colligan, Trevor T. Robinson, Declan C. Nolan, Yang Hua, Weijuan Cao

Publikováno v: Colligan, A, Robinson, T T, Nolan, D C, Hua, Y & Cao, W 2022, ' Hierarchical CADNet: Learning from B-Reps for Machining Feature Recognition ', CAD Computer Aided Design, vol. 147, no. 103226, 103226 . https://doi.org/10.1016/j.cad.2022.103226

Deep learning approaches have been shown to be capable of recognizing shape features (e.g. machining features) in Computer-Aided Design (CAD) models in certain circumstances, yet still have issues when the features intersect, and in exploiting the ge

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::18c83982dba4ca0dd674abeae557b6da
https://pure.qub.ac.uk/en/publications/0aeb13bf-fe2b-46a0-907f-d5ba499ab305

Point Cloud Dataset Creation for Machine Learning on CAD Models

Autor: Declan Nolan, Andrew R. Colligan, Trevor T. Robinson, Yang Hua

Publikováno v: Colligan, A R, Robinson, T T, Nolan, D C & Hua, Y 2021, ' Point cloud dataset creation for machine learning on CAD models ', Computer-Aided Design and Applications, vol. 18, no. 4, pp. 760-771 . https://doi.org/10.14733/cadaps.2021.760-771

Recently, the application of machine learning on Computer-Aided Design (CAD) models has emerged. However, there is a lack of robust methods for the conversion of boundary representation (B-Rep) CAD models from engineering software to appropriate inpu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::29abe3a673b27184fba09ed40c7d97e8
https://doi.org/10.14733/cadconfp.2020.152-156