Research on Fast Detection Method of Wind Turbine in Remote Sensing Image Land Area Based on Yolo-Reference-Cited by-同舟云学术

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Research on Fast Detection Method of Wind Turbine in Remote Sensing Image Land Area Based on Yolo

Published:2023-07-16 Issue: Volume: Page:
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Container-title:IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Chen Deliang¹,Cheng Taotao¹,Lu Yanyan²,Gao Kyle³,Fatholahi Sarah³,Li Jonathan³

Affiliation:

1. Nanjing University of Posts and Telecommunications,College of Geographic and Biologic Information,Nanjing,JS,China,210023

2. Nanjing Audit University,Institute of Natural Resources and Environment Audit,Nanjing,JS,China,211815

3. University of Waterloo,Department of Geography and Environmental Management,Waterloo,ON,Canada,N2L 3G1

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10281394/10281399/10281442.pdf?arnumber=10281442

Reference15 articles.

1. Fast R-CNN

2. Rich feature hierarchies for accurate object detection and semantic segmentation;girshick;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2014

3. Spatial pyramid pooling in deep convolutional networks for visual recognition;he;IEEE Transactions on Pattern Analysis and Machine Intelligence,2015

4. Faster r-cnn: Towards real-time object detection with region proposal networks;ren;Advances in neural information processing systems,2015

5. YOLOv7: Trainable bag-of-freebies sets new state of the art for real time object detectors;wang,2022

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