Local keypoint-based Faster R-CNN-Reference-Cited by-同舟云学术

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Local keypoint-based Faster R-CNN

Published:2020-04-28 Issue:10 Volume:50 Page:3007-3022
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Ding Xintao^ORCID,Li Qingde,Cheng Yongqiang,Wang Jinbao,Bian Weixin,Jie Biao

Funder

Anhui Provincial Natural Science Foundation

National Natural Science Foundation of China

University of Hull 'Evolving a Plastics Circular Economy' project

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-020-01665-9.pdf

Reference38 articles.

1. Cai Z, Vasconcelos N (2018) Cascade R-CNN: Delving into high quality object detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 6154–6162

2. Krizhevsky A, Sutskever I, Hinton GE (2017) ImageNet classification with deep convolutional neural networks. Commun ACM 60(6):84–90

3. Girshick R (2015) Fast R-CNN. In: Proceedings of the IEEE international conference on computer vision, pp 1440–1448

4. Ren S, He K, Girshick R, Sun J (2017) Faster R-CNN: Towards real-time object detection with region proposal networks. IEEE Trans Pattern Anal Mach Intell 39(6):1137–1149

5. Redmon J, Farhadi A (2017) Yolo9000: better, faster, stronger. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7263–7271

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