Deep Learning Algorithms for Human Activity Recognition in Manual Material Handling Tasks.

RCNN performed similarly (95.9%; 89.2%) with a positive trend with subject numerosity.

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In this case, the average F1-score shows a slightly increasing trend with increasing subject numbers. 4.3.

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In the 70-30 split training, the BiLSTM and RCNN performed similarly, but the RCNN showed an increasing trend of the F1-score as the number of subjects in the dataset increased, suggesting that it could result in higher classification performances with more subjects.

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