UCR-SSL: Uncertainty-Based Consistency Regularization for Semi-Supervised Learning-Reference-Cited by-同舟云学术

UCR-SSL: Uncertainty-Based Consistency Regularization for Semi-Supervised Learning

Published:2023-02-05 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Electronics, Information, and Communication (ICEIC)
language:
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Author:

Lee Seungil¹,Kim Hyun¹,Chun Dayoung²

Affiliation:

1. Seoul National University of Science and Technology,Research Center for Electrical and Information Technology,Department of Electrical and Information Engineering,Seoul,Korea

2. Seoul National University,Inter-University Semiconductor Research Center,Department of Electrical and Computer Engineering,Seoul,Korea

Funder

Technology Development

National Research Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10049840/10049805/10049938.pdf?arnumber=10049938

Reference14 articles.

1. Consistency-based semi- supervised learning for object detection;jeong;Advances in neural information processing systems,2019

2. Improved regularization of convolutional neural networks with cutout;devries;arXiv preprint arXiv 1708 04552,2017

3. On calibration of modern neural networks;guo;Int Conference on Machine Learning,2017

4. Regularization with stochastic transformations and perturbations for deep semi-supervised learning;sajjadi;Advances in neural information processing systems,2016

5. End-to-End Semi-Supervised Object Detection with Soft Teacher

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