YOLO（二）：Overview
2020/12/25
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https://pixabay.com/zh/photos/yolo-life-neon-letters-on-2817390/
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◎ Abstract
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◎ Introduction
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本論文要解決（它之前研究）的（哪些）問題（弱點）？
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# A Survey of Deep Learning-based Object Detection
說明：
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◎ Method
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解決方法？
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# YOLO。
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具體細節？
https://hemingwang.blogspot.com/2021/05/yoloillustrated.html
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◎ Result
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本論文成果。
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◎ Discussion
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本論文與其他論文（成果或方法）的比較。
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成果比較。
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方法比較。
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◎ Conclusion
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◎ Future Work
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後續相關領域的研究。
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後續延伸領域的研究。
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◎ References
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# Faster R-CNN。被引用 23747 次。
Ren, Shaoqing, et al. "Faster r-cnn: Towards real-time object detection with region proposal networks." Advances in neural information processing systems. 2015.
https://proceedings.neurips.cc/paper/2015/file/14bfa6bb14875e45bba028a21ed38046-Paper.pdf
# YOLO。被引用 12295 次。
Redmon, Joseph, et al. "You only look once: Unified, real-time object detection." Proceedings of the IEEE conference on computer vision and pattern recognition. 2016.
# Mask R-CNN。被引用 8887 次。
He, Kaiming, et al. "Mask r-cnn." Proceedings of the IEEE international conference on computer vision. 2017.
https://openaccess.thecvf.com/content_ICCV_2017/papers/He_Mask_R-CNN_ICCV_2017_paper.pdf
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# A Survey of Deep Learning-based Object Detection
Jiao, Licheng, et al. "A survey of deep learning-based object detection." IEEE Access 7 (2019): 128837-128868.
https://arxiv.org/pdf/1907.09408.pdf
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