Author of the publication

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation.

L. Chen, R. Lopes, B. Cheng, M. Collins, E. Cubuk, B. Zoph, H. Adam, and J. Shlens. ECCV (9), volume 12354 of Lecture Notes in Computer Science, page 695-714. Springer, (2020)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Ekin Celik

Ekin Kozal

Halis Ruhi Ekingen

Seyhan Cubukcu

Turhan Cubukcu

Other publications of authors with the same name

Realistic Evaluation of Semi-Supervised Learning Algorithms.A. Oliver, A. Odena, C. Raffel, E. Cubuk, and I. Goodfellow. ICLR (Workshop), OpenReview.net, (2018)Improving Robustness Without Sacrificing Accuracy with Patch Gaussian AugmentationR. Lopes, D. Yin, B. Poole, J. Gilmer, and E. Cubuk. (2019)cite arxiv:1906.02611.Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation.L. Chen, R. Lopes, B. Cheng, M. Collins, E. Cubuk, B. Zoph, H. Adam, and J. Shlens. ECCV (9), volume 12354 of Lecture Notes in Computer Science, page 695-714. Springer, (2020)Multi-Task Self-Training for Learning General Representations.G. Ghiasi, B. Zoph, E. Cubuk, Q. Le, and T. Lin. ICCV, page 8836-8845. IEEE, (2021)End-to-End Differentiable Reactive Molecular Dynamics Simulations Using JAX.M. Kaymak, S. Schoenholz, E. Cubuk, K. O'Hearn, K. Jr., and H. Aktulga. ISC, volume 13948 of Lecture Notes in Computer Science, page 202-219. Springer, (2023)AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty.D. Hendrycks, N. Mu, E. Cubuk, B. Zoph, J. Gilmer, and B. Lakshminarayanan. CoRR, (2019)Learning Data Augmentation Strategies for Object Detection.B. Zoph, E. Cubuk, G. Ghiasi, T. Lin, J. Shlens, and Q. Le. ECCV (27), volume 12372 of Lecture Notes in Computer Science, page 566-583. Springer, (2020)AutoAugment: Learning Augmentation Strategies From Data.E. Cubuk, B. Zoph, D. Mané, V. Vasudevan, and Q. Le. CVPR, page 113-123. Computer Vision Foundation / IEEE, (2019)Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation.G. Ghiasi, Y. Cui, A. Srinivas, R. Qian, T. Lin, E. Cubuk, Q. Le, and B. Zoph. CoRR, (2020)Affinity and Diversity: Quantifying Mechanisms of Data Augmentation.R. Lopes, S. Smullin, E. Cubuk, and E. Dyer. CoRR, (2020)

BibSonomy

Disambiguation of "Cubuk, Ekin D."

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation.

Please choose a person to relate this publication to

Ekin Celik

Ekin Kozal

Halis Ruhi Ekingen

Seyhan Cubukcu

Turhan Cubukcu

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Cubuk, Ekin D."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation.

Please choose a person to relate this publication to

Ekin Celik

Ekin Kozal

Halis Ruhi Ekingen

Seyhan Cubukcu

Turhan Cubukcu

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation.