2022
Karim, Nazmul; Rizve, Mamshad Nayeem; Rahnavard, Nazanin; Mian, Ajmal; Shah, Mubarak
UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learning Conference
IEEE Computer Vision and Pattern Recognition, 2022.
Tags: Contrastive Learning, CVPR, Noisy Labels, Semi-supervised learning | Links:
@conference{nokey_102,
title = {UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learning},
author = {Nazmul Karim and Mamshad Nayeem Rizve and Nazanin Rahnavard and Ajmal Mian and Mubarak Shah},
url = {https://www.crcv.ucf.edu/wp-content/uploads/2018/11/07363.pdf
https://www.crcv.ucf.edu/wp-content/uploads/2018/11/07363-supp.pdf
https://github.com/nazmul-karim170/unicon-noisy-label},
year = {2022},
date = {2022-06-19},
urldate = {2022-06-19},
publisher = {IEEE Computer Vision and Pattern Recognition},
keywords = {Contrastive Learning, CVPR, Noisy Labels, Semi-supervised learning},
pubstate = {published},
tppubtype = {conference}
}
Karim, Nazmul; Rizve, Mamshad Nayeem; Rahnavard, Nazanin; Mian, Ajmal; Shah, Mubarak
UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learning Conference
IEEE Computer Vision and Pattern Recognition, 2022.
Tags: Contrastive Learning, CVPR, Noisy Labels, Semi-supervised learning | Links:
@conference{nokey_150,
title = {UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learning},
author = {Nazmul Karim and Mamshad Nayeem Rizve and Nazanin Rahnavard and Ajmal Mian and Mubarak Shah},
url = {https://www.crcv.ucf.edu/wp-content/uploads/2018/11/07363.pdf
https://www.crcv.ucf.edu/wp-content/uploads/2018/11/07363-supp.pdf
https://github.com/nazmul-karim170/unicon-noisy-label},
year = {2022},
date = {2022-06-19},
urldate = {2022-06-19},
publisher = {IEEE Computer Vision and Pattern Recognition},
keywords = {Contrastive Learning, CVPR, Noisy Labels, Semi-supervised learning},
pubstate = {published},
tppubtype = {conference}
}
0000
Test Bachelor Thesis
0000.
Tags: Crowd Analysis, Damage Assessment, DIVA, Drone Video Analysis, EEG/Brain, Incremental Learning, Learning with Less Labels, LIDAR, Multi-Modal Learning, Noisy Labels, Open World, Out of Distribution (OOD), Privacy Preservation, Pseudo-Labeling, SAR, Self-Joint Learning, Semi-supervised learning, Tiny Actions, Video Synopsis, Video Synthesis, View-Invariance, Weakly Supervised Learning, Wildlife Preservation
@bachelorthesis{nokey_135,
title = {Test},
keywords = {Crowd Analysis, Damage Assessment, DIVA, Drone Video Analysis, EEG/Brain, Incremental Learning, Learning with Less Labels, LIDAR, Multi-Modal Learning, Noisy Labels, Open World, Out of Distribution (OOD), Privacy Preservation, Pseudo-Labeling, SAR, Self-Joint Learning, Semi-supervised learning, Tiny Actions, Video Synopsis, Video Synthesis, View-Invariance, Weakly Supervised Learning, Wildlife Preservation},
pubstate = {published},
tppubtype = {bachelorthesis}
}
Test Bachelor Thesis
0000.
Tags: Crowd Analysis, Damage Assessment, DIVA, Drone Video Analysis, EEG/Brain, Incremental Learning, Learning with Less Labels, LIDAR, Multi-Modal Learning, Noisy Labels, Open World, Out of Distribution (OOD), Privacy Preservation, Pseudo-Labeling, SAR, Self-Joint Learning, Semi-supervised learning, Tiny Actions, Video Synopsis, Video Synthesis, View-Invariance, Weakly Supervised Learning, Wildlife Preservation
@bachelorthesis{nokey_171,
title = {Test},
keywords = {Crowd Analysis, Damage Assessment, DIVA, Drone Video Analysis, EEG/Brain, Incremental Learning, Learning with Less Labels, LIDAR, Multi-Modal Learning, Noisy Labels, Open World, Out of Distribution (OOD), Privacy Preservation, Pseudo-Labeling, SAR, Self-Joint Learning, Semi-supervised learning, Tiny Actions, Video Synopsis, Video Synthesis, View-Invariance, Weakly Supervised Learning, Wildlife Preservation},
pubstate = {published},
tppubtype = {bachelorthesis}
}