Beyond Active Learning: Leveraging the Full Potential of Human Interaction via Auto-Labeling, Human Correction, and Human Verification-Reference-Cited by-同舟云学术

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Beyond Active Learning: Leveraging the Full Potential of Human Interaction via Auto-Labeling, Human Correction, and Human Verification

Published:2024-01-03 Issue: Volume:34 Page:2869-2877
ISSN:
Container-title:2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
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Author:

Beck Nathan¹,Killamsetty Krishnateja¹,Kothawade Suraj¹,Iyer Rishabh¹

Affiliation:

1. University of Texas,Dallas

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10483279/10483282/10483705.pdf?arnumber=10483705

Reference20 articles.

1. k-means++: The advantages of careful seeding;Arthur;Technical report, Stanford,2006

2. GONE FISHING

3. Deep batch active learning by diverse, uncertain gradient lower bounds;Ash,2019

4. Effective evaluation of deep active learning on image classification tasks;Beck,2021

5. An analysis of single-layer networks in unsupervised feature learning;Coates

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Advancing allergy source mapping: A comprehensive multidisciplinary framework integrating machine learning, graph theory and game theory;Applied Soft Computing;2024-11

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