InceptionDepth-wiseYOLOv2: improved implementation of YOLO framework for pedestrian detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Media Technology,Information Systems
Link
https://link.springer.com/content/pdf/10.1007/s13735-022-00239-4.pdf
Reference46 articles.
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3. Zhu C, Peng Y (2015) A boosted multi-task model for pedestrian detection with occlusion handling. IEEE Trans Image Process 24(12):5619–5629. https://doi.org/10.1109/TIP.2015.2483376
4. Cao J, Pang Y, Li X (2017) Learning multilayer channel features for pedestrian detection. IEEE Trans Image Process 26(7):3210–3220. https://doi.org/10.1109/TIP.2017.2694224
5. Li J, Liang X, Shen S, Xu T, Feng J, Yan S (2017) Scale-aware fast R-CNN for pedestrian detection. IEEE Trans Multimedia 20(4):985–996. https://doi.org/10.1109/TMM.2017.2759508
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