Confidence-based Deep Multimodal Fusion for Activity Recognition
Author:
Affiliation:
1. School of Integrated Technology, Yonsei University, Incheon, Korea
2. School of Integrated Technology, Yonsei University. Incheon, Korea
Funder
Ministry of Science and ICT
Ministry of Science ICT and Future Planning
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3267305.3267522
Reference23 articles.
1. The Opportunity challenge: A benchmark database for on-body sensor-based activity recognition
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3. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
4. Impact of Three-Dimensional Video Scalability on Multi-View Activity Recognition using Deep Learning
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