2019
DOI: 10.1080/01691864.2019.1635910
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Pedestrian trajectory prediction using BiRNN encoder–decoder framework

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Cited by 13 publications
(1 citation statement)
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“…where p m represents the mean of accuracy and r m represents the mean of recall. e proposed automated model was compared with Bi-LSTM [42], CNN [43], and BiRNN [44] on the above three publicly available datasets, and the experimental results are shown in Figure 6. It can be seen that the performance of the method in this paper on two datasets (MSR and CTB7) is significantly better than the other methods.…”
Section: Micro F1mentioning
confidence: 99%
“…where p m represents the mean of accuracy and r m represents the mean of recall. e proposed automated model was compared with Bi-LSTM [42], CNN [43], and BiRNN [44] on the above three publicly available datasets, and the experimental results are shown in Figure 6. It can be seen that the performance of the method in this paper on two datasets (MSR and CTB7) is significantly better than the other methods.…”
Section: Micro F1mentioning
confidence: 99%