A two-stream conditional generative adversarial network for improving semantic predictions in urban driving scenes
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Published:2024-07
Issue:
Volume:133
Page:108290
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ISSN:0952-1976
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Container-title:Engineering Applications of Artificial Intelligence
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language:en
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Short-container-title:Engineering Applications of Artificial Intelligence
Author:
Lateef F.,
Kas M.ORCID,
Chahi A.ORCID,
Ruichek Y.
Reference61 articles.
1. Improving road semantic segmentation using generative adversarial network;Abdollahi;IEEE Access,2021
2. Classifier aided training for semantic segmentation;Ahmed;J. Vis. Commun. Image Represent.,2021
3. Bertasius, G., Shi, J., Torresani, L., 2016. Semantic segmentation with boundary neural fields. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 3602–3610.
4. Least Absolute Deviations: Theory, Applications, and Algorithms;Bloomfield,1983
5. Borse, S., Wang, Y., Zhang, Y., Porikli, F., 2021. Inverseform: A loss function for structured boundary-aware segmentation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 5901–5911.