Robust multi-modal pedestrian detection using deep convolutional neural network with ensemble learning model
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Published:2024-09
Issue:
Volume:249
Page:123527
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ISSN:0957-4174
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Container-title:Expert Systems with Applications
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language:en
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Short-container-title:Expert Systems with Applications
Author:
Kumar Jain Deepak,
Zhao Xudong,
Garcia SalvadorORCID,
Neelakandan Subramani
Reference38 articles.
1. Aledhari, M., Razzak, R., Parizi, R. M., & Srivastava, G. (2021, April). Multimodal machine learning for pedestrian detection. 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring). Presented at the 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), Helsinki, Finland. doi:10.1109/vtc2021-spring51267.2021.9448692.
2. Multi-modal machine learning for pedestrian detection;Aledhari,2021
3. Design guidelines on deep learning–based pedestrian detection methods for supporting autonomous vehicles;Boukerche;ACM Computing Surveys,2022
4. Attention fusion for one-stage multispectral pedestrian detection;Cao;Sensors,2021
5. Survey of pedestrian action recognition techniques for autonomous driving;Chen;Tsinghua Science and Technology,2020
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