Zobrazeno 1 - 4
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pro vyhledávání: '"Hanieh Naderi"'
Autor:
Hanieh Naderi, Ivan V. Bajic
Publikováno v:
IEEE Access, Vol 11, Pp 144274-144295 (2023)
Deep learning has successfully solved a wide range of tasks in 2D vision as a dominant AI technique. Recently, deep learning on 3D point clouds has become increasingly popular for addressing various tasks in this field. Despite remarkable achievement
Externí odkaz:
https://doaj.org/article/980f79f2e9e44f0dbbabda514d746a0b
Publikováno v:
PLoS ONE, Vol 18, Iss 2, p e0271388 (2023)
The 3D point clouds are increasingly being used in various application including safety-critical fields. It has recently been demonstrated that deep neural networks can successfully process 3D point clouds. However, these deep networks can be misclas
Externí odkaz:
https://doaj.org/article/34eaa733a8e1466a83913af7d2b470b0
Although 3D point cloud classification has recently been widely deployed in different application scenarios, it is still very vulnerable to adversarial attacks. This increases the importance of robust training of 3D models in the face of adversarial
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f0b811223a6e1a7560a7a8b4bc92efc
http://arxiv.org/abs/2202.11287
http://arxiv.org/abs/2202.11287
Publikováno v:
2020 International Conference on Machine Vision and Image Processing (MVIP).
Convolution Neural Networks (CNNs), despite being one of the most successful image classification methods, are not robust to most geometric transformations (rotation, isotropic scaling) because of their structural constraints. Recently, scale steerab