Multi-Task Learning with Task-Specific Feature Filtering in Low-Data Condition

Multi-Task Learning with Task-Specific Feature Filtering in Low-Data Condition

Multi-task learning is a computationally efficient method to solve multiple tasks in one multi-task model, instead of multiple single-task models. MTL is expected to learn both diverse and shareable visual features from multiple datasets. However, MTL performances usually do not outperform single-ta...

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Bibliographic Details
Main Authors: Sang-woo Lee, Ryong Lee, Min-seok Seo, Jong-chan Park, Hyeon-cheol Noh, Jin-gi Ju, Rae-young Jang, Gun-woo Lee, Myung-seok Choi, Dong-geol Choi
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Electronics
Subjects:
deep learning
multi-task learning
convolutional neural network
Online Access:https://www.mdpi.com/2079-9292/10/21/2691

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https://www.mdpi.com/2079-9292/10/21/2691

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