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Active learning for multimedia

Proceedings of the 15th ACM international conference on Multimedia, 2007
Active learning improves the performance of classification or search systems by adding humans to the loop. It aims at optimizing the production of the class labels that are necessary for supervised learning. The proposed tutorial responds to a strong need for the integration of this technique in multimedia indexing and retrieval systems.
openaire   +1 more source

A Survey of Deep Active Learning

ACM Computing Surveys, 2022
Pengzhen Ren   +2 more
exaly  

A Survey on Active Deep Learning: From Model Driven to Data Driven

ACM Computing Surveys, 2022
Peng Liu, Lizhe Wang, Rajiv Ranjan
exaly  

Bayesian deep-learning for RUL prediction: An active learning perspective

Reliability Engineering and System Safety, 2022
Rong Zhu, Weiwen Peng, Zhi-Sheng Ye
exaly  

Activity and Children's Learning

Child Development, 1974
P, Wolff, J R, Levin, E T, Longobardi
openaire   +2 more sources

Efficient Active Learning by Querying Discriminative and Representative Samples and Fully Exploiting Unlabeled Data

IEEE Transactions on Neural Networks and Learning Systems, 2021
Bin Gu, Zhou Zhai, Cheng Deng
exaly  

Active learning of linearly parametrized interatomic potentials

Computational Materials Science, 2017
Evgeny V Podryabinkin   +1 more
exaly  

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