GLFE-YOLOX: Global and Local Feature Enhanced YOLOX for Remote Sensing Images-Reference-Cited by-同舟云学术

GLFE-YOLOX: Global and Local Feature Enhanced YOLOX for Remote Sensing Images

Published:2024 Issue: Volume:73 Page:1-12
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Gu Qiang¹^ORCID,Huang Haisong²^ORCID,Han Zhenggong¹^ORCID,Fan Qingsong¹^ORCID,Li Yiting³^ORCID

Affiliation:

1. School of Key Laboratory of Advanced Manufacturing Technology, Ministry of Education, Guizhou University, Guizhou, China

2. School of Key Laboratory of Advanced Manufacturing Technology, Ministry of Education, and the State Key Laboratory of Public Bid Data, Guizhou University, Guizhou, China

3. College of Big Data Statistics, Guizhou University of Finance and Economics, Guizhou, China

Funder

National Natural Science Foundation of China

Guizhou Provincial Science and Technology Projects

Natural Science Foundation of Chongqing

Open Fund Project through the Key Laboratory of Advanced Manufacturing Technology Ministry of Education, China

Guizhou Provincial Department of Education

Joint Open Fund of Guizhou Provincial Department of Education

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/19/10367905/10497138.pdf?arnumber=10497138

Reference50 articles.

1. Pattern planning and design of tiger hazelnut shrub in urban ecosystem based on remote sensing technology

2. Multitarget Detection and Tracking Method in Remote Sensing Satellite Video

3. Backpropagation Applied to Handwritten Zip Code Recognition

4. You Only Look Once: Unified, Real-Time Object Detection

5. YOLO9000: Better, Faster, Stronger

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