SV-Learner: Support-Vector Contrastive Learning for Robust Learning With Noisy Labels-Reference-Cited by-同舟云学术

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SV-Learner: Support-Vector Contrastive Learning for Robust Learning With Noisy Labels

Published:2024-10 Issue:10 Volume:36 Page:5409-5422
ISSN:1041-4347
Container-title:IEEE Transactions on Knowledge and Data Engineering
language:
Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

Liang Xin¹^ORCID,Ji Yanli²^ORCID,Zheng Wei-Shi³^ORCID,Zuo Wangmeng⁴^ORCID,Zhu Xiaofeng²^ORCID

Affiliation:

1. Shenzhen Institute for Advanced Study, UESTC, Shenzhen, China

2. School of Computer Science and Engineering, UESTC, Chengdu, China

3. School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China

4. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China

Funder

Science and Technology Innovation Committee of Shenzhen Municipality Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/69/10679113/10495194.pdf?arnumber=10495194

Reference67 articles.

1. EfficientNet: Rethinking model scaling for convolutional neural networks;Tan

2. Deep Kinematics Analysis for Monocular 3D Human Pose Estimation

3. You Only Look Once: Unified, Real-Time Object Detection

4. Faster R-CNN: Towards real-time object detection with region proposal networks;Ren

5. Deep Residual Learning for Image Recognition

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