Published September 8, 2021
| Version
v8
Dataset
Open
TAD-Net: An Approach for Realtime Action Detection Based on TCN and GCN in Digital Twin Shop-floor
Creators
Description
We proposed a real-time detection approach for shop-floor production action, this approach took the sequence data of continuous human skeleton joints sequence as input, reconstructed the Joint Classification-Regression Recurrent Neural Networks (JCR-RNN) based on Temporal Convolution Network (TCN) and Graph Convolution Network (GCN), constructed our Temporal Action Detection Net (TAD-Net), realized real-time shop-floor production action detection.
Files
confuseMatrix1.csv
Files
(108.7 MB)
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Checksum: md5:4afb207cbcb25747a6a498a5ceb98c6f
PID: http://hdl.handle.net/11304/d5f7195d-7145-4251-af3e-571c461c448b |
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Checksum: md5:e99b261f430ac957dabaf71c82e21fdc
PID: http://hdl.handle.net/11304/e6642661-5662-4ecb-abda-eb11bfd5f014 |
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Checksum: md5:db601b78791cf447aebfea544a666fcd
PID: http://hdl.handle.net/11304/02f79781-a07a-4de9-b992-86be4245011f |
108.7 MB | Download |
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Checksum: md5:44fdd80ed94cad255bdc276eea049c2e
PID: http://hdl.handle.net/11304/3981e658-1c7d-48d1-9700-3d4faba29a06 |
34.7 kB | Download |
Additional details
Identifiers
- B2SHARE Legacy Record ID
- 354187c2a0754fee873023e724dd9055
- B2SHARE Legacy Record ID
- 74fdf3108e0343f786be84fba8592654
InGRID metadata
- Access
- Freely accessible for non-commercial use
- Data providers
- Qing Hong
- Guidelines for use available
- True
- Indicators available
- True
- Search or browse function available online
- True
- Text documents available
- True