Pyramid Scene Parsing Network for Driver Distraction Classification
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-48573-2_27
Reference9 articles.
1. Chen, S., Song, Y., Su, J., Fang, Y., Shen, L., Mi, Z., Su, B.: Segmentation of field grape bunches via an improved pyramid scene parsing network. Int. J. Agric. Biol. Eng. 14(6), 185–194 (2021). https://doi.org/10.25165/ijabe.v14i6.6903. https://www.ijabe.org/index.php/ijabe/article/view/6903
2. Cheng, B., Chen, L.C., Wei, Y., Zhu, Y., Huang, Z., Xiong, J., Huang, T.S., Hwu, W.M., Shi, H.: SPGNet: semantic prediction guidance for scene parsing, pp. 5218–5228 (2019). https://openaccess.thecvf.com/content_ICCV_2019/html/Cheng_SPGNet_Semantic_Prediction_Guidance_for_Scene_Parsing_ICCV_2019_ paper.html
3. Ersal, T., Fuller, H.J.A., Tsimhoni, O., Stein, J.L., Fathy, H.K.: Model-based analysis and classification of driver distraction under secondary tasks. IEEE Trans. Intell. Transp. Syst. 11(3), 692–701 (2010). https://doi.org/10.1109/TITS.2010.2049741
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5. Long, X., Zhang, W., Zhao, B.: PSPNet-SLAM: a semantic SLAM detect dynamic object by pyramid scene parsing network. IEEE Access 8, 214685–214695 (2020). https://doi.org/10.1109/ACCESS.2020.3041038,conferenceName:IEEEAccess
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