Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Phi Vu Tran"'
Autor:
Phi Vu Tran
Few-shot object detection (FSOD) is an emerging problem aimed at detecting novel concepts from few exemplars. Existing approaches to FSOD assume abundant base labels to adapt to novel objects. This paper studies the task of semi-supervised FSOD by co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f5194837f0c822c3e6dd35b37e89bd53
Autor:
Rouzbeh Abbassi, Shadi Abpeikar, Hossein Adel, Sreenatha Anavatti, Ivan Bakhshayeshi, Nima Bayat-Makou, Amin Beheshti, Rhiannon Blake, Bahareh Dabirmanesh, Eila Erfani, Milad Rabbabni Esfahani, Karu P. Esselle, Zahra Falahati, Helia Farhood, Vikram Garaniya, Matthew Garratt, Omid Ghaffarpasand, Ebrahim Ghasemy, A. Yagmur Goren, Supriya Gupta, Asghar Habibnejad Korayem, Bavly Hanna, Ahmad Hosseinzadeh, Majid Ilchi Ghazaan, Ahmad Miri Jahromi, Alexandros Karatopouzis, Elika Karbassiyazdi, Kathryn Kasmarik, Khosro Khajeh, Md Mohiuddin Khan, Alireza Khataee, Mohammad Khedri, Ahmed A. Kishk, Ali Lalbakhsh, Reza Maleki, Yamini Mittal, Sweta Modak, Masoud Mohseni-Dargah, Hadi Mokarizadeh, Parisa Nasrollahi, Arman Nedjati, Matineh Pooshideh, Yaşar K. Recepoğlu, Nabi Rezvani, Roy B.V.B. Simorangkir, Pratiksha Srivastava, Firouzeh Taghikhah, Sara Tayari, Phi Vu Tran, Mohammad Yazdi, Esmaeil Zarei
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3182f900c9fa2a9b37ac4c5f9bb6c7b8
https://doi.org/10.1016/b978-0-323-90508-4.01002-9
https://doi.org/10.1016/b978-0-323-90508-4.01002-9
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030975456
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::41961ab1f1c3bba7c0283b8d092a8365
https://doi.org/10.1007/978-3-030-97546-3_43
https://doi.org/10.1007/978-3-030-97546-3_43
Autor:
Phi Vu Tran
Publikováno v:
CVPR
Recent years have seen flourishing research on both semi-supervised learning and 3D room layout reconstruction. In this work, we explore the intersection of these two fields to advance the research objective of enabling more accurate 3D indoor scene
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5d845f6908cab3bb7f1120f4cdda1057
https://doi.org/10.1109/cvpr46437.2021.01510
https://doi.org/10.1109/cvpr46437.2021.01510
Autor:
Phi Vu Tran
Publikováno v:
DSAA
We examine two fundamental tasks associated with graph representation learning: link prediction and semi-supervised node classification. We present a novel autoencoder architecture capable of learning a joint representation of both local graph struct
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c69b050fa1753da760d3f5e0c81c3d0
http://arxiv.org/abs/1802.08352
http://arxiv.org/abs/1802.08352
Autor:
Phi Vu Tran
Publikováno v:
Military Operations Research. 18:53-62
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::78485b4d60d1a460bd8389f75b3ba7cd
https://doi.org/10.5711/1082598318353
https://doi.org/10.5711/1082598318353